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Found results for
patents
1.
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SYSTEMS AND METHODS FOR VIDEO OBJECT SEGMENTATION
Document Number |
03199370 |
Status |
Pending |
Filing Date |
2021-11-17 |
Open to Public Date |
2022-05-27 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Homayounfar, Namdar
- Ma, Wei-Chiu
- Urtasun, Raquel
- Liang, Justin
|
Abstract
Systems and methods for generating object segmentations across videos are provided. An example system can enable an annotator to identify objects within a first image frame of a video sequence by clicking anywhere within the object. The system processes the first image frame and a second, subsequent, image frame to assign each pixel of the second image frame to one of the objects identified in the first image frame or the background. The system refines the resulting object masks for the second image frame using a recurrent attention module based on contextual features extracted from the second image frame. The system receives additional user input for the second image frame and uses the input, in combination with the object masks for the second image frame, to determine object masks for a third, subsequent, image frame in the video sequence. The process is repeated for each image in the video sequence.
IPC Classes ?
- G01S 7/48 - RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - Details of systems according to groups , , of systems according to group
- G01S 7/486 - Receivers
- G01S 13/93 - Radar or analogous systems, specially adapted for specific applications for anti-collision purposes
- G01S 17/93 - Lidar systems, specially adapted for specific applications for anti-collision purposes
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2.
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AUTOMATIC ANNOTATION OF OBJECT TRAJECTORIES IN MULTIPLE DIMENSIONS
Document Number |
03139421 |
Status |
Pending |
Filing Date |
2021-11-17 |
Open to Public Date |
2022-05-17 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Yang, Bin
- Liang, Ming
- Zeng, Wenyuan
- Bai, Min
- Urtasun, Raquel
|
Abstract
Techniques for improving the performance of an autonomous vehicle (AV) by automatically annotating objects surrounding the AV are described herein. A system can obtain sensor data from a sensor coupled to the AV and generate an initial object trajectory for an object using the sensor data, Additionally, the systern can detemiine a fixed value for the object size of the object based on the initial object trajectory. Moreover, the system can generate an updated initial object trajectory, wherein the object size cotresponds to the fixed value. Furthermore, the system can determine, based on the sensor data and the updated initial object trajectory, a refined object trajectory. Subsequently, the system can generate a multi- dimensional label for the object based on the refined object trajectory. A motion plan for controlling the AV can be generated based on the multi-dimensional label.
IPC Classes ?
- G01C 21/20 - Instruments for performing navigational calculations
- B60W 30/095 - Predicting travel path or likelihood of collision
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- B60W 30/08 - Predicting or avoiding probable or impending collision
- G05D 1/02 - Control of position or course in two dimensions
- G01S 17/93 - Lidar systems, specially adapted for specific applications for anti-collision purposes
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3.
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SYSTEMS AND METHODS FOR SIMULATING TRAFFIC SCENES
Document Number |
03139477 |
Status |
Pending |
Filing Date |
2021-11-17 |
Open to Public Date |
2022-05-17 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Tan, Shuhan
- Wong, Kelvin Ka Wing
- Wang, Shenlong
- Manivasagam, Sivabalan
- Ren, Mengye
- Urtasun, Raquel
|
Abstract
Example aspects of the present disclosure describe a scene generator for simulating scenes in an environment. For example, snapshots of simulated traffic scenes can be generated by sampling a joint probability distribution trained on real- world trotfic scenes. In some implementations, samples of the joint probability distribution can be obtained by sampling a plurality of factorized probability distributions for a plurality of objects for sequential insertion into the scene.
IPC Classes ?
- G01C 21/28 - Navigation; Navigational instruments not provided for in groups specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G05D 1/02 - Control of position or course in two dimensions
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4.
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SYSTEMS AND METHODS FOR GENERATING SYNTHETIC MOTION PREDICTIONS
Document Number |
03139480 |
Status |
Pending |
Filing Date |
2021-11-17 |
Open to Public Date |
2022-05-17 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Suo, Shun Da
- Lozano, Sebastian David Regalado
- Casas, Sergio
- Urtasun, Raquel
|
Abstract
Systems and methods for generating synthetic testing data for autonomous vehicles are provided, A computing system can obtain map data descriptive of an environment and object data descriptive of a plurality of objects within the environment. The computing system can generate context data including deep or latent features extracted from the map and object data by one or more machine-learned models. The computing system can process the context data with a machine-leamed model to generate synthetic motion prediction for the plurality of objects. The synthetic motion predictions for the objects can include one or more synthesized states for the objects at future times, The computing system can provide, as an output, synthetic testing data that includes the plurality of synthetic niotion predictions for the objects. The synthetic testing data can be used to test an autonomous vehicle control system in a simulation.
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5.
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GENERATING MOTION SCENARIOS FOR SELF-DRIVING VEHICLES
Document Number |
03139449 |
Status |
Pending |
Filing Date |
2021-11-17 |
Open to Public Date |
2022-05-17 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Wang, Jingkang
- Pun, Ava Alison
- Tu, Xuanyuan
- Ren, Mengye
- Sadat, Abbas
- Casas, Sergio
- Manivasagam, Sivabalan
- Urtasun, Raquel
|
Abstract
Techniques for generating testing data for an autonomous vehicle (AV) are described herein. A system can obtain sensor data descriptive of a traffic scenario. The traffic scenario can include a subject vehicle and actors in an environment. Additionally, the system can generate a perturbed trajectory for a first actor in the environment based on perturbation values. lVforeover, the systern can generate sirnulated sensor data. The simulated sensor data can include data descriptive of the perturbed trajectoiy for the first actor in the environment. Furthermore, the system can provide the simulated sensor data as input to an AV control system. The AV control system can be configured to process the simulated sensor data to generate an updated trajectory for the subject vehicle in the environment. Subsequently, the system can evaluate an adversarial loss function based on the updated trajectory for the subject vehicle to generate an adversarial loss value.
IPC Classes ?
- G05B 23/02 - Electric testing or monitoring
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- G05D 1/02 - Control of position or course in two dimensions
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6.
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SYSTEMS AND METHODS FOR ACTOR MOTION FORECASTING WITHIN A SURROUNDING ENVIRONMENT OF AN AUTONOMOUS VEHICLE
Document Number |
03139481 |
Status |
Pending |
Filing Date |
2021-11-17 |
Open to Public Date |
2022-05-17 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Zeng, Wenyuan
- Liang, Ming
- Liao, Renjie
- Urtasun, Raquel
|
Abstract
Systems and methods are provided for forecasting the motion of actors within a surrounding environment of an autonomous platform. For example, a computing system of an autonomous platform can use machine-learned model(s) to generate actor- specific graphs with past motions of actors and the local map topology. The computing system can project the actor-specific graphs of all actors to a global graph. The global graph can allow the computing system to determine which actors may interact with one another by propagating information over the global graph. The computing system can distribute the interactions determined using the global graph to the individual actor-specific graphs. The computing system can then predict a motion trajectory for an actor based on the associated actor-specific graph, which captures the actor-to-actor interactions and actor-to-map relations.
IPC Classes ?
- G08G 9/02 - Anti-collision systems
- B60W 30/09 - Taking automatic action to avoid collision, e.g. braking and steering
- B60W 30/095 - Predicting travel path or likelihood of collision
- G06N 20/00 - Machine learning
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- G08G 1/16 - Anti-collision systems
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7.
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SYSTEMS AND METHODS FOR MOTION FORECASTING AND PLANNING FOR AUTONOMOUS VEHICLES
Document Number |
03139575 |
Status |
Pending |
Filing Date |
2021-11-17 |
Open to Public Date |
2022-05-17 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Cui, Alexander Yuhao
- Sadat, Abbas
- Casas, Sergio
- Liao, Renjie
- Urtasun, Raquel
|
Abstract
Systems and methods are disclosed for motion forecasting and planning for autonomous vehicles. For example, a plurality of future traffic scenarios are determined by modeling a joint distribution of actor trajectories for a plurality of actors, as opposed to an approach that models actors individually. As another example, a diversity objective is evaluated that rewards sampling of the future traffic scenarios that require distinct reactions from the autonomous vehicle. An estimated probability for the plurality of future traffic scenarios can be determined and used to generate a contingency plan for motion of the autonomous vehicle. The contingency plan can include at least one initial short-term trajectory intended for immediate action of the AV and a plurality of subsequent long-term trajectories associated with the plurality of future traffic scenarios.
IPC Classes ?
- G08G 9/02 - Anti-collision systems
- B60W 30/09 - Taking automatic action to avoid collision, e.g. braking and steering
- B60W 30/095 - Predicting travel path or likelihood of collision
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- G08G 1/16 - Anti-collision systems
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8.
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SYSTEMS AND METHODS FOR SIMULTANEOUS LOCALIZATION AND MAPPING USING ASYNCHRONOUS MULTI-VIEW CAMERAS
Document Number |
03136909 |
Status |
Pending |
Filing Date |
2021-10-29 |
Open to Public Date |
2022-04-30 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Yang, Anqi Joyce
- Cui, Can
- Barsan, Ioan Andrei
- Wang, Shenlong
- Urtasun, Raquel
|
Abstract
Systems and methods for the simultaneous localization and mapping of autonomous vehicle systems are provided. A method includes receiving a plurality of input image frames from the plurality of asynchronous image devices triggered at different times to capture the plurality of input image frames. The method includes identifying reference image frame(s) corresponding to a respective input image frame by matching the field of view of the respective input image frame to the fields of view of the reference image frame(s). The method includes determining association(s) between the respective input image frame and three- dimensional map point(s) based on a comparison of the respective input image frame to the one or more reference image frames. The method includes generating an estimated pose for the autonomous vehicle the one or more three-dimensional map points. The method includes updating a continuous-time motion model of the autonomous vehicle based on the estimated pose.
IPC Classes ?
- G05D 1/02 - Control of position or course in two dimensions
- G06T 7/70 - Determining position or orientation of objects or cameras
- G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- B60W 30/10 - Path keeping
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9.
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SYSTEMS AND METHODS FOR GENERATING BASIS PATHS FOR AUTONOMOUS VEHICLE MOTION CONTROL
Document Number |
03192462 |
Status |
In Force |
Filing Date |
2021-09-10 |
Open to Public Date |
2022-03-17 |
Grant Date |
2023-09-05 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Liu, Chenggang
- Bradley, David Mcallister
- Jia, Daoyuan
|
Abstract
Systems and methods for basis path generation are provided. In particular, a computing system can obtain a target nominal path. The computing system can determine a current pose for an autonomous vehicle. The computing system can determine, based at least in part on the current pose of the autonomous vehicle and the target nominal path, a lane change region. The computing system can determine one or more merge points on the target nominal path. The computing system can, for each respective merge point in the one or more merge points, generate a candidate basis path from the current pose of the autonomous vehicle to the respective merge point. The computing system can generate a suitability classification for each candidate basis path. The computing system can select one or more candidate basis paths based on the suitability classification for each respective candidate basis path in the plurality of candidate basis paths.
IPC Classes ?
- B60W 30/00 - Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- G01C 21/26 - Navigation; Navigational instruments not provided for in groups specially adapted for navigation in a road network
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10.
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LIGHT DETECTION AND RANGING (LIDAR) SYSTEM HAVING TRANSMIT OPTICS FOR PRE-COLLIMATION STEERING
Document Number |
03188460 |
Status |
Pending |
Filing Date |
2021-08-06 |
Open to Public Date |
2022-02-10 |
Owner |
UATC, LLC (USA)
|
Inventor |
Millischer, Martin
|
Abstract
A LIDAR system is provided. The LIDAR system includes a plurality of emitters respectively configured to emit a light signal along a transmit path. The LIDAR system includes a plurality of optics positioned along the transmit path. The plurality of optics includes a collimator optic having a primary optical power along a first axis. The plurality of optics further include one or more transmit optics positioned along the transmit path between the plurality of emitters and the collimator optic. Furthermore, the one or more transmit optics have a primary optical power along a second axis.
IPC Classes ?
- G01S 7/481 - Constructional features, e.g. arrangements of optical elements
- G01S 17/931 - Lidar systems, specially adapted for specific applications for anti-collision purposes of land vehicles
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11.
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SYSTEMS AND METHODS FOR SENSOR DATA PACKET PROCESSING AND SPATIAL MEMORYUPDATING FOR ROBOTIC PLATFORMS
Document Number |
03126236 |
Status |
Pending |
Filing Date |
2021-07-28 |
Open to Public Date |
2022-01-29 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Frossard, Davi Eugenio Nascimento
- Suo, Shun Da
- Casas, Sergio
- Tu, Xuanyuan
- Urtasun, Raquel
|
Abstract
Systems and methods for streaming sensor packets in real-time are provided. An example method includes obtaining a sensor data packet representing a first portion of a three-hundred and sixty degree view of a surrounding environment of a robotic platform. The method includes generating, using machine-learned model(s), a local feature map based at least in part on the sensor data packet. The local feature map is indicative of local feature(s) associated with the first portion of the three-hundred and sixty degree view. The method includes updating, based at least in part on the local feature map, a spatial map to include the local feature(s). The spatial map includes previously extracted local features associated with a previous sensor data packet representing a different portion of the three-hundred and sixty degree view than the first portion. The method includes determining an object within the surrounding environment based on the updated spatial map.
IPC Classes ?
- G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G01S 17/89 - Lidar systems, specially adapted for specific applications for mapping or imaging
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12.
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COMPRESSION OF MACHINE-LEARNED MODELS BY VECTOR QUANTIZATION
Document Number |
03126245 |
Status |
Pending |
Filing Date |
2021-07-28 |
Open to Public Date |
2022-01-29 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Covarrubias, Julieta Martinez
- Shewakramani, Jashan
- Liu, Ting Wei
- Zeng, Wenyuan
- Urtasun, Raquel
|
Abstract
A computing system can include one or more processors and one or more computer- readable media storing instructions that, when executed by the one or more processors, cause the computing system to perform operations including obtaining model structure data indicative of a plurality of parameters of a machine-learned model; determining a codebook comprising a plurality of centroids, the plurality of centroids having a respective index of a plurality of indices indicative of an ordering of the codebook; determining a plurality of codes respective to the plurality of parameters, the plurality of codes respectively comprising a code index of the plurality of indices corresponding to a closest centroid of the plurality of centroids to a respective parameter of the plurality of parameters; and providing encoded data as an encoded representation of the plurality of parameters of the machine-learned model, the encoded data comprising the codebook and the plurality of codes.
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13.
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RECOVERING AND SIMULATING PEDESTRIANS IN THE WILD
Document Number |
03126250 |
Status |
Pending |
Filing Date |
2021-07-28 |
Open to Public Date |
2022-01-29 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Yang, Ze
- Manivasagam, Sivabalan
- Liang, Ming
- Ma, Wei-Chiu
- Yang, Bin
- Urtasun, Raquel
|
Abstract
Systems and methods for generating simulation data based on real-world dynamic objects are provided. A method includes obtaining two- and three-dimensional data descriptive of a dynamic object in the real world. The two- and three- dimensional information can be provided as an input to a machine-learned model to receive object model parameters descriptive of a pose and shape modification with respect to a three-dimensional template object model. The parameters can represent a three-dimensional dynamic object model indicative of an object pose and an object shape for the dynamic object. The method can be repeated on sequential two- and three-dimensional information to generate a sequence of object model parameters over time. Portions of a sequence of parameters can be stored as simulation data descriptive of a simulated trajectory of a unique dynamic object. The parameters can be evaluated by an objective function to refine the parameters and train the machine-learned model.
IPC Classes ?
- G06V 20/00 - Scenes; Scene-specific elements
- G06N 20/00 - Machine learning
- G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
- G06V 20/56 - Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
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14.
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LIGHT DETECTION AND RANGING (LIDAR) SYSTEM
Document Number |
03176996 |
Status |
Pending |
Filing Date |
2021-04-26 |
Open to Public Date |
2021-11-04 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Ignatescu, Florin Cornel
- Gruver, Daniel Fredric
- Pennecot, Gaetan
|
Abstract
A LIDAR system is provided. The LIDAR system includes an emitter. The emitter includes a light source and one or more lenses positioned along a transmit path. The light source is configured to emit a primary laser beam through the one or more lenses in the transmit path to provide a transmit beam. The LIDAR system includes a receiver spaced apart from the emitter. The receiver includes one or more lenses positioned along a receive path such that the one or more lenses receive a reflected laser beam. The LIDAR system includes an optical element positioned along the transmit path. The optical element is configured to direct a portion of the primary laser beam in a direction towards the receive path as a secondary laser beam.
IPC Classes ?
- G01S 7/481 - Constructional features, e.g. arrangements of optical elements
- G01S 17/931 - Lidar systems, specially adapted for specific applications for anti-collision purposes of land vehicles
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15.
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SYSTEM AND METHODS FOR CONTROLLING STATE TRANSITIONS USING A VEHICLE CONTROLLER
Document Number |
03174307 |
Status |
Pending |
Filing Date |
2021-03-30 |
Open to Public Date |
2021-10-07 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Tschanz, Frederic
- Naik, Maitreya Jayesh
- Yanakiev, Diana
- Greenfield, Aaron L.
- Poeppel, Scott C.
|
Abstract
The present disclosure is directed to controlling state transitions in an autonomous vehicle. In particular, a computing system can initiate the autonomous vehicle into a no-authorization state upon startup. The computing system can receive an authorization request. The computing system determines whether the authorization request includes a request to enter the first or second mode of operations, wherein the first mode of operations is associated with the autonomous vehicle being operated without a human operator and the second mode of operations is associated with the autonomous vehicle being operable by a human operator. The computing system can transition the autonomous vehicle from the no-authorization state into a standby state in response to determining the authorization request includes a request to enter the first mode of operations or into a manual-controlled state in response to determining the authorization request is a request to enter the second mode of operations.
IPC Classes ?
- B60W 50/00 - CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - Details of control systems for road vehicle drive control not related to the control of a particular sub-unit
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
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16.
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AUTONOMOUS VEHICLE COMPUTING SYSTEM WITH PROCESSING ASSURANCE
Document Number |
03207403 |
Status |
Pending |
Filing Date |
2021-02-26 |
Open to Public Date |
2021-10-07 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Hyde, Sean
- Molinari, Jose Francisco
- Thomas, Stephen Luke
|
Abstract
Systems and methods are directed to a method for assured autonomous vehicle compute processing. The method can include providing sensor data to first and second functional circuitry of an autonomy computing system. The first and second functional circuitry can be configured to generate first and second outputs associated with a first autonomous compute function. The method can include generating, by the first and second functional circuitry in response to the sensor data, first and second output data associated with the first autonomous compute function. The method can include generating, by monitoring circuitry of the autonomy computing system, comparative data associated with differences between the first output data and the second output data. The method can include generating one or more vehicle control signals for the autonomous vehicle based at least in part on the comparative data.
IPC Classes ?
- G05D 1/85 - Fail-safe operations, e.g. limp home mode
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- B60W 50/04 - Monitoring the functioning of the control system
- G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B 23/02 - Electric testing or monitoring
- G06N 3/02 - Neural networks
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17.
|
AUTONOMOUS VEHICLE COMPUTING SYSTEM WITH PROCESSING ASSURANCE
Document Number |
03174273 |
Status |
In Force |
Filing Date |
2021-02-26 |
Open to Public Date |
2021-10-07 |
Grant Date |
2023-09-12 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Hyde, Sean
- Molinari, Jose Francisco
- Thomas, Stephen Luke
|
Abstract
Systems and methods are directed to a method for assured autonomous vehicle compute processing. The method can include providing sensor data to first and second functional circuitry of an autonomy computing system. The first and second functional circuitry can be configured to generate first and second outputs associated with a first autonomous compute function. The method can include generating, by the first and second functional circuitry in response to the sensor data, first and second output data associated with the first autonomous compute function. The method can include generating, by monitoring circuitry of the autonomy computing system, comparative data associated with differences between the first output data and the second output data. The method can include generating one or more vehicle control signals for the autonomous vehicle based at least in part on the comparative data.
IPC Classes ?
- G05D 1/228 - Command input arrangements located on-board unmanned vehicles
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- G05B 13/00 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05D 1/242 - Means based on the reflection of waves generated by the vehicle (using passive navigation aids external to the vehicle G05D 1/244;using signals provided by artificial sources external to the vehicle G05D 1/247)
- G05D 1/43 - Control of position or course in two dimensions
- G05D 1/80 - Arrangements for reacting to or preventing system or operator failure (handing over between remote control and on-board control, or handing over between remote control arrangements G05D 1/227)
- G06N 3/02 - Neural networks
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18.
|
AUTONOMOUS VEHICLE COMPUTING SYSTEM WITH PROCESSING ASSURANCE
Document Number |
03207406 |
Status |
In Force |
Filing Date |
2021-02-26 |
Open to Public Date |
2021-10-07 |
Grant Date |
2024-02-27 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Hyde, Sean
- Molinari, Jose Francisco
- Thomas, Stephen Luke
|
Abstract
Systems and methods are directed to a method for assured autonomous vehicle compute processing. The method can include providing sensor data to first and second functional circuitry of an autonomy computing system. The first and second functional circuitry can be configured to generate first and second outputs associated with a first autonomous compute function. The method can include generating, by the first and second functional circuitry in response to the sensor data, first and second output data associated with the first autonomous compute function. The method can include generating, by monitoring circuitry of the autonomy computing system, comparative data associated with differences between the first output data and the second output data. The method can include generating one or more vehicle control signals for the autonomous vehicle based at least in part on the comparative data.
IPC Classes ?
- G05D 1/85 - Fail-safe operations, e.g. limp home mode
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- B60W 50/04 - Monitoring the functioning of the control system
- G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B 23/02 - Electric testing or monitoring
- G06N 3/02 - Neural networks
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19.
|
COMPUTER SYSTEM FOR UTILIZING ULTRASONIC SIGNALS TO IMPLEMENT OPERATIONS FOR AUTONOMOUS VEHICLES
Document Number |
03173446 |
Status |
Pending |
Filing Date |
2021-02-16 |
Open to Public Date |
2021-09-30 |
Owner |
UATC, LLC (USA)
|
Inventor |
Fetter, Jacob
|
Abstract
In some examples, a control system for a vehicle can detect a set of ultrasonic signals generated by a mobile computing device of a user. Additionally, the control system can determine a pin code from the set of ultrasonic signals. Moreover, the control system can perform one or more vehicle operations to initiate fulfillment of a transport request that is associated with the determined pin code, upon the user being determined to be within a given proximity distance of the vehicle.
IPC Classes ?
- H04W 4/024 - Guidance services
- H04W 4/40 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- B60R 25/01 - Fittings or systems for preventing or indicating unauthorised use or theft of vehicles operating on vehicle systems or fittings, e.g. on doors, seats or windscreens
- G01S 5/18 - Position-fixing by co-ordinating two or more direction or position-line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
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20.
|
SYSTEM AND METHOD FOR AUTONOMOUS VEHICLE SYSTEMS SIMULATION
Document Number |
03170637 |
Status |
Pending |
Filing Date |
2021-02-26 |
Open to Public Date |
2021-09-10 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Urtasun, Raquel
- Wong, Kelvin Ka Wing
- Zhang, Qiang
- Yang, Bin
- Liang, Ming
- Liao, Renjie
|
Abstract
Systems and methods of the present disclosure are directed to a method. The method can include obtaining simplified scenario data associated with a simulated scenario. The method can include determining, using a machine-learned perception-prediction simulation model, a simulated perception-prediction output based at least in part on the simplified scenario data. The method can include evaluating a loss function comprising a perception loss term and a prediction loss term. The method can include adjusting one or more parameters of the machine-learned perception-prediction simulation model based at least in part on the loss function.
IPC Classes ?
- B60W 30/095 - Predicting travel path or likelihood of collision
- B60W 40/04 - Traffic conditions
- G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
- G06F 11/30 - Monitoring
- G06F 11/36 - Preventing errors by testing or debugging of software
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21.
|
SYSTEMS AND METHODS FOR VEHICLE-TO-VEHICLE COMMUNICATIONS FOR IMPROVED AUTONOMOUS VEHICLE OPERATIONS
Document Number |
03158601 |
Status |
Pending |
Filing Date |
2020-11-16 |
Open to Public Date |
2021-05-20 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Manivasagam, Sivabalan
- Liang, Ming
- Yang, Bin
- Zeng, Wenyuan
- Urtasun, Raquel
- Wang, Tsun-Hsuan
|
Abstract
Systems and methods for vehicle-to-vehicle communications are provided. An example computer-implemented method includes obtaining, by a computing system onboard a first autonomous vehicle, sensor data associated with an environment of the first autonomous vehicle. The method includes determining, by the computing system, an intermediate environmental representation of at least a portion of the environment of the first autonomous vehicle based at least in part on the sensor data. The method includes generating, by the computing system, a compressed intermediate environmental representation by compressing the intermediate environmental representation of at least the portion of the environment of the first autonomous vehicle. The method includes communicating, by the computing system, the compressed intermediate environmental representation to a second autonomous vehicle.
IPC Classes ?
- G05D 1/247 - using signals provided by artificial sources external to the vehicle, e.g. navigation beacons
- H04W 4/46 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
- G08G 1/01 - Detecting movement of traffic to be counted or controlled
- G08G 1/16 - Anti-collision systems
- G05D 1/226 - Communication links with the remote-control arrangements
- G05D 1/242 - Means based on the reflection of waves generated by the vehicle (using passive navigation aids external to the vehicle G05D 1/244;using signals provided by artificial sources external to the vehicle G05D 1/247)
- G06N 3/0464 - Convolutional networks [CNN, ConvNet]
|
22.
|
CONDITIONAL ENTROPY CODING FOR EFFICIENT VIDEO COMPRESSION
Document Number |
03158597 |
Status |
In Force |
Filing Date |
2020-11-16 |
Open to Public Date |
2021-05-20 |
Grant Date |
2023-07-11 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Liu, Jerry Junkai
- Wang, Shenlong
- Ma, Wei-Chiu
- Urtasun, Raquel
|
Abstract
The present disclosure is directed to video compression using conditional entropy coding. An ordered sequence of image frames can be transformed to produce an entropy coding for each image frame. Each of the entropy codings provide a compressed form of image information based on a prior image frame and a current image frame (the current image frame occurring after the prior image frame). In this manner, the compression model can capture temporal relationships between image frames or encoded representations of the image frames using a conditional entropy encoder trained to approximate the joint entropy between frames in the image frame sequence.
IPC Classes ?
- H04N 19/463 - Embedding additional information in the video signal during the compression process by compressing encoding parameters before transmission
- H04N 19/91 - Entropy coding, e.g. variable length coding [VLC] or arithmetic coding
|
23.
|
PERCEPTION AND MOTION PREDICTION FOR AUTONOMOUS DEVICES
Document Number |
03134772 |
Status |
Pending |
Filing Date |
2020-03-23 |
Open to Public Date |
2020-10-01 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Liang, Ming
- Yang, Bin
- Chen, Yun
- Urtasun, Raquel
|
Abstract
Systems, methods, tangible non-transitory computer-readable media, and devices associated with object perception and prediction of object motion are provided. For example, a plurality of temporal instance representations can be generated. Each temporal instance representation can be associated with differences in the appearance and motion of objects over past time intervals. Past paths and candidate paths of a set of objects can be determined based on the temporal instance representations and current detections of objects. Predicted paths of the set of objects using a machine-learned model trained that uses the past paths and candidate paths to determine the predicted paths. Past path data that includes information associated with the predicted paths can be generated for each object of the set of objects respectively.
IPC Classes ?
- G05D 1/633 - Dynamic obstacles
- G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- G05D 1/248 - generated by satellites, e.g. GPS
- G05D 1/43 - Control of position or course in two dimensions
- G06N 20/00 - Machine learning
- G06Q 50/40 - Business processes related to the transportation industry (shipping G06Q 10/83)
|
24.
|
SYSTEMS AND METHODS FOR GENERATING SYNTHETIC SENSOR DATA VIA MACHINE LEARNING
Document Number |
03134819 |
Status |
Pending |
Filing Date |
2020-03-23 |
Open to Public Date |
2020-10-01 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Manivasagam, Sivabalan
- Wang, Shenlong
- Ma, Wei-Chiu
- Wong, Kelvin Ka Wing
- Zeng, Wenyuan
- Urtasun, Raquel
|
Abstract
The present disclosure provides systems and methods that combine physics-based systems with machine learning to generate synthetic LiDAR data that accurately mimics a real-world LiDAR sensor system. In particular, aspects of the present disclosure combine physics-based rendering with machine-learned models such as deep neural networks to simulate both the geometry and intensity of the LiDAR sensor. As one example, a physics-based ray casting approach can be used on a three-dimensional map of an environment to generate an initial three-dimensional point cloud that mimics LiDAR data. According to an aspect of the present disclosure, a machine-learned model can predict one or more dropout probabilities for one or more of the points in the initial three-dimensional point cloud, thereby generating an adjusted three-dimensional point cloud which more realistically simulates real-world LiDAR data.
|
25.
|
DEPTH ESTIMATION FOR AUTONOMOUS DEVICES
Document Number |
03134771 |
Status |
Pending |
Filing Date |
2020-03-23 |
Open to Public Date |
2020-10-01 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Duggal, Shivam
- Wang, Shenlong
- Ma, Wei-Chiu
- Urtasun, Raquel
|
Abstract
Systems, methods, tangible non-transitory computer-readable media, and devices associated with depth estimation are provided. For example, a feature representation associated with stereo images including a first and second plurality of points can be accessed. Sparse disparity estimates associated with disparities between the first and second plurality of points can be determined. The sparse disparity estimates can be based on machine-learned models that estimate disparities based on comparisons of the first plurality of points to the second plurality of points. Confidence ranges associated with the disparities between the first and second plurality of points can be determined based on the sparse disparity estimates and the machine-learned models. A disparity map for the stereo images can be generated based on using the confidence ranges and machine-learned models to prune the disparities outside the confidence ranges. Furthermore, three-dimensional depth estimates associated with the stereo images can be generated based on the disparity map.
IPC Classes ?
- G06T 7/593 - Depth or shape recovery from multiple images from stereo images
|
26.
|
COMPRESSION OF IMAGES HAVING OVERLAPPING FIELDS OF VIEW USING MACHINE-LEARNED MODELS
Document Number |
03134773 |
Status |
In Force |
Filing Date |
2020-03-23 |
Open to Public Date |
2020-10-01 |
Grant Date |
2023-01-03 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Liu, Jerry Junkai
- Wang, Shenlong
- Urtasun, Raquel
|
Abstract
A machine-learned image compression model includes a first encoder configured to generate a first image code based at least in part on first image data. The first encoder includes a first series of convolutional layers configured to generate a first series of respective feature maps based at least in part on the first image. A second encoder is configured to generate a second image code based at least in part on second image data and includes a second series of convolutional layers configured to generate a second series of respective feature maps based at least in part on the second image and disparity-warped feature data. Respective parametric skip functions associated convolutional layers of the second series are configured to generate disparity -warped feature data based at least in part on disparity associated with the first series of respective feature maps and the second series of respective feature maps.
IPC Classes ?
- H04N 19/597 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding specially adapted for multi-view video sequence encoding
|
27.
|
VEHICLE ROUTING WITH LOCAL AND GENERAL ROUTES
Document Number |
03127823 |
Status |
Pending |
Filing Date |
2020-01-24 |
Open to Public Date |
2020-07-30 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Nagy, Bryan John
- Goldman, Brent
- Dean, Robert Michael S
- Voznesensky, Michael
- Wen, Jian
- Zhao, Yanbo
|
Abstract
Various examples are directed to systems and methods for controlling an autonomous vehicle. For example, a navigator system at an autonomous vehicle may generate a plurality of local routes beginning at a vehicle location and extending to a plurality of local route end points. The navigator system may access general route cost data, the general route cost data describing general route costs from the plurality of local route end points to a trip end point. The navigator system may select the first local route of the plurality of routes based at least in part on the general route cost data. A vehicle autonomy system at the autonomous vehicle may begin to control the autonomous vehicle along the first local route.
|
28.
|
LIDAR SYSTEM DESIGN TO MITIGATE LIDAR CROSSTALK
Document Number |
03110727 |
Status |
Pending |
Filing Date |
2019-07-25 |
Open to Public Date |
2020-02-06 |
Owner |
UATC, LLC (USA)
|
Inventor |
Juelsgaard, Soren
|
Abstract
Aspects of the present disclosure involve systems, methods, and devices for mitigating Lidar cross-talk. Consistent with some embodiments, a Lidar system is configured to include one or more noise source detectors that detect noise signals that may produce noise in return signals received at the Lidar system. A noise source detector comprises a light sensor to receive a noise signal produced by a noise source and a timing circuit to provide a timing signal indicative of a direction of the noise source relative to an autonomous vehicle on which the Lidar system is mounted. A noise source may be an external Lidar system or a surface in the surrounding environment that is reflecting light signals such as those emitted by an external Lidar system.
IPC Classes ?
- G01S 17/87 - Combinations of systems using electromagnetic waves other than radio waves
- G01S 17/93 - Lidar systems, specially adapted for specific applications for anti-collision purposes
|
29.
|
SYSTEMS AND METHODS FOR CHANGING A DESTINATION OF AN AUTONOMOUS VEHICLE IN REAL-TIME
Document Number |
03074464 |
Status |
Pending |
Filing Date |
2018-08-27 |
Open to Public Date |
2019-03-07 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Nix, Molly Castle
- Chin, Sean
- Zhao, Dennis
- Maliksi, Joseph
|
Abstract
Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data representing a first location associated with a service request. The method includes controlling the autonomous vehicle to travel in accordance with a first route that leads to the first location. The method includes determining a second location for the service request when the autonomous vehicle is en route to the first location. The method includes controlling the autonomous vehicle to provide the requested service at the second location.
IPC Classes ?
- G06Q 50/40 - Business processes related to the transportation industry (shipping G06Q 10/83)
- G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G08G 1/09 - Arrangements for giving variable traffic instructions
- G05D 1/225 - operated by off-board computers
|
30.
|
AUTONOMOUS VEHICLE COLLISION MITIGATION SYSTEMS AND METHODS
Document Number |
03068317 |
Status |
Pending |
Filing Date |
2018-06-22 |
Open to Public Date |
2019-01-03 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Wood, Matthew Shaw
- Leach, William M.
- Poeppel, Scott C.
- Letwin, Nicholas G.
- Zych, Noah
|
Abstract
Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes obtaining, from an autonomy system, data indicative of a planned trajectory of the autonomous vehicle through a surrounding environment. The method includes determining a region of interest in the surrounding environment based at least in part on the planned trajectory. The method includes controlling one or more first sensors to obtain data indicative of the region of interest. The method includes identifying one or more objects in the region of interest, based at least in part on the data obtained by the one or more first sensors. The method includes controlling the autonomous vehicle based at least in part on the one or more objects identified in the region of interest.
IPC Classes ?
- G05D 1/228 - Command input arrangements located on-board unmanned vehicles
- B60W 30/09 - Taking automatic action to avoid collision, e.g. braking and steering
- B62D 15/02 - Steering position indicators
- G05D 1/242 - Means based on the reflection of waves generated by the vehicle (using passive navigation aids external to the vehicle G05D 1/244;using signals provided by artificial sources external to the vehicle G05D 1/247)
- G05D 1/246 - using environment maps, e.g. simultaneous localisation and mapping [SLAM]
- G05D 1/43 - Control of position or course in two dimensions
- G05D 1/622 - Obstacle avoidance (predicting or avoiding probable or impending collision of road vehicles B60W 30/08)
|
31.
|
MULTI-MODAL SWITCHING ON A COLLISION MITIGATION SYSTEM
Document Number |
03013157 |
Status |
In Force |
Filing Date |
2018-08-01 |
Open to Public Date |
2018-10-02 |
Grant Date |
2019-05-07 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Wood, Matthew Shaw
- Leach, William M.
- Poeppel, Scott C.
- Letwin, Nicholas G.
- Zych, Noah
|
Abstract
Systems and methods for controlling an autonomous vehicle are provided. In one example embodiment, a computer-implemented method includes receiving data indicative of an operating mode of the vehicle, wherein the vehicle is configured to operate in a plurality of operating modes. The method includes determining one or more response characteristics of the vehicle based at least in part on the operating mode of the vehicle, each response characteristic indicating how the vehicle responds to a potential collision. The method includes controlling the vehicle based at least in part on the one or more response characteristics.
IPC Classes ?
- B60W 30/09 - Taking automatic action to avoid collision, e.g. braking and steering
|
32.
|
VEHICLE CONTROL SYSTEM
Document Number |
03054555 |
Status |
Pending |
Filing Date |
2018-02-19 |
Open to Public Date |
2018-08-30 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Jones, Morgan D.
- Dacko, Michael John
- Kirby, Brian Thomas
|
Abstract
Systems and methods for controlling a failover response of an autonomous vehicle are provided. In one example embodiment, a method includes determining, by one or more computing devices on-board an autonomous vehicle, an operational mode of the autonomous vehicle. The autonomous vehicle is configured to operate in at least a first operational mode in which a human driver is present in the autonomous vehicle and a second operational mode in which the human driver is not present in the autonomous vehicle. The method includes detecting a triggering event associated with the autonomous vehicle and determining actions to be performed by the autonomous vehicle in response to the triggering event based at least in part on the operational mode. The method includes providing one or more control signals to one or more of the systems on-board the autonomous vehicle to perform the one or more actions responsive to the triggering event.
IPC Classes ?
- G05D 1/228 - Command input arrangements located on-board unmanned vehicles
- B60W 50/029 - Adapting to failures or work around with other constraints, e.g. circumvention by avoiding use of failed parts
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- G05B 7/02 - Arrangements for obtaining smooth engagement or disengagement of automatic control electric
- G05D 1/22 - Command input arrangements
- G05D 1/80 - Arrangements for reacting to or preventing system or operator failure (handing over between remote control and on-board control, or handing over between remote control arrangements G05D 1/227)
- G05D 1/227 - Handing over between remote control and on-board control; Handing over between remote control arrangements
|
33.
|
COLLISION-AVOIDANCE SYSTEM FOR AUTONOMOUS-CAPABLE VEHICLES
Document Number |
03008091 |
Status |
In Force |
Filing Date |
2018-06-13 |
Open to Public Date |
2018-08-15 |
Grant Date |
2019-09-24 |
Owner |
UATC, LLC (USA)
|
Inventor |
Gray, Andrew
|
Abstract
A collision-avoidance system for use with an autonomous-capable vehicle can continuously receive image frames captured of the roadway to determine drivable space in a forward direction of the vehicle. The system can determine, for each image frame, whether individual regions of the image frame depict drivable space. The system can do so using machine-learned image recognition algorithms such as convolutional neural networks generated using extensive training data. Using such techniques, the system can label regions of the image frames as corresponding to drivable space or non-drivable space. By analyzing the labeled image frames, the system can determine whether the vehicle is likely to impact a region of non- drivable space. And, in response to such a determination, the system can generate control signals that override other control systems or human operator input to control the brakes, the steering, or other sub-systems of the vehicle to avoid the collision.
IPC Classes ?
- B60W 30/09 - Taking automatic action to avoid collision, e.g. braking and steering
- B60W 30/095 - Predicting travel path or likelihood of collision
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- B60W 30/10 - Path keeping
- B60W 30/14 - Cruise control
|
34.
|
VEHICLE SERVICING SYSTEM
Document Number |
03047086 |
Status |
In Force |
Filing Date |
2017-12-12 |
Open to Public Date |
2018-06-21 |
Grant Date |
2023-07-25 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Poeppel, Scott C.
- Letwin, Nicholas G.
- Kelly, Sean J.
|
Abstract
Systems and methods for addressing a user-reported vehicle condition are provided. In one example embodiment, a method includes receiving a service request for a vehicle service for a user. The service request is indicative of a location associated with the user. The method includes sending first control signal(s) to an autonomous vehicle that is configured to provide the vehicle service. The first control signal(s) indicate that the autonomous vehicle is to travel to the location associated with the user. The method includes receiving a communication indicative of an existence of a condition that reduces a suitability of the autonomous vehicle to provide the vehicle service. The condition is identified by the user. The method includes determining action(s) to be performed by the autonomous vehicle based, at least in part, on the existence of the condition. The method includes sending second control signal(s) to the autonomous vehicle to perform the action(s).
IPC Classes ?
- G06Q 10/20 - Administration of product repair or maintenance
- B60S 5/00 - Servicing, maintaining, repairing, or refitting of vehicles
- G07C 5/00 - Registering or indicating the working of vehicles
|
35.
|
VEHICLE MANAGEMENT SYSTEM
Document Number |
03047095 |
Status |
Pending |
Filing Date |
2017-12-12 |
Open to Public Date |
2018-06-21 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Poeppel, Scott C.
- Letwin, Nicholas G.
- Kelly, Sean J.
|
Abstract
Systems, methods, and vehicles for taking a vehicle out-of-service are provided. A method includes obtaining, by one or more computing devices on-board an autonomous vehicle, data indicative of one or more parameters associated with the autonomous vehicle. The autonomous vehicle is configured to provide a vehicle service to one or more users of the vehicle service. The method includes determining, by the computing devices, an existence of a fault associated with the autonomous vehicle based at least in part on the one or more parameters associated with the autonomous vehicle. The method includes determining, by the computing devices, one or more actions to be performed by the autonomous vehicle based at least in part on the existence of the fault. The method includes performing, by the computing devices, one or more of the actions to take the autonomous vehicle out-of-service based at least in part on the fault.
IPC Classes ?
- G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
|
36.
|
NEURAL NETWORK SYSTEM FOR AUTONOMOUS VEHICLE CONTROL
Document Number |
03038542 |
Status |
In Force |
Filing Date |
2017-10-12 |
Open to Public Date |
2018-04-26 |
Grant Date |
2020-06-02 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Djuric, Nemanja
- Houston, John
|
Abstract
A neural network may be utilized for autonomously driving a self-driving vehicle (SDV). The neural network can establish a destination location in local coordinates relative to the SDV. The neural network may then identify one or more navigation points in a forward operational direction of the SDV, and process sensor data from a sensor system of the SDV, the sensor data providing a sensor view of the forward operational direction of the SDV. Utilizing the sensor data, the neural network can operate acceleration, braking, and steering systems of the SDV to continuously follow the one or more navigation points along an established route to the destination location.
IPC Classes ?
- G01C 21/20 - Instruments for performing navigational calculations
|
37.
|
AUTONOMOUS VEHICLE CONTROL USING SUBMAPS
Document Number |
03029742 |
Status |
In Force |
Filing Date |
2017-07-01 |
Open to Public Date |
2018-01-04 |
Grant Date |
2023-03-07 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Browning, Brett
- Milstein, Adam
- Hansen, Peter
- Eade, Ethan
- Prasser, David
- Larose, David
- Zlot, Robert
- Melik-Barkhudarov, Narek
- Bagnell, James Andrew
|
Abstract
A system to use submaps to control operation of a vehicle is disclosed. A storage system may be provided with a vehicle to store a collection of submaps that represent a geographic area where the vehicle may be driven. A programmatic interface may be provided to receive submaps and submap updates independently of other submaps.
IPC Classes ?
- G01C 21/20 - Instruments for performing navigational calculations
- G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
|
38.
|
PLANAR-BEAM, LIGHT DETECTION AND RANGING SYSTEM
Document Number |
03015894 |
Status |
In Force |
Filing Date |
2017-03-02 |
Open to Public Date |
2017-09-08 |
Grant Date |
2019-02-26 |
Owner |
UATC, LLC (USA)
|
Inventor |
Boehmke, Scott
|
Abstract
A planar-beam, light detection and ranging (PLADAR) system can include a laser scanner that emits a planar-beam, and a detector array that detects reflected light from the planar beam.
IPC Classes ?
- G01S 7/48 - RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - Details of systems according to groups , , of systems according to group
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- B60W 30/10 - Path keeping
- G01S 7/497 - Means for monitoring or calibrating
- H03M 1/12 - Analogue/digital converters
|
39.
|
INTENTION SIGNALING FOR AN AUTONOMOUS VEHICLE
Document Number |
03015338 |
Status |
In Force |
Filing Date |
2016-12-23 |
Open to Public Date |
2017-08-31 |
Grant Date |
2019-10-15 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Ross, William Payne
- Liu, Chenggang
- Sweeney, Matthew
- Pilarski, Thomas
|
Abstract
An intention signaling system for an autonomous vehicle (AV) can monitor sensor information indicating a situational environment of the AV, and detect an external entity based, at least in part, on the sensor data. The intention signaling system can generate an output to signal one of an intent of the AV or an acquiescence of the AV to the external entity.
IPC Classes ?
- B60W 30/14 - Cruise control
- B60W 50/14 - Means for informing the driver, warning the driver or prompting a driver intervention
- B60Q 1/02 - Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to illuminate the way ahead or to illuminate other areas of way or environments
- B60W 40/02 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to ambient conditions
|
40.
|
OPTIMIZING COMMUNICATION FOR AUTOMATED VEHICLES
Document Number |
03005673 |
Status |
In Force |
Filing Date |
2016-12-08 |
Open to Public Date |
2017-06-15 |
Grant Date |
2023-03-07 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Ross, William
- Aitken, Michael
|
Abstract
A backend system for a fleet of autonomous vehicles (AVs) for a given region can store a spectrum heat map indicating network coverage strength for a plurality of network types sourced at base stations located throughout the given region. The backend system can dynamically receive network quality data from the plurality of AVs traveling throughout the given region, and dynamically update the spectrum heat map based on the received network quality data.
IPC Classes ?
- H04W 48/20 - Selecting an access point
- H04W 24/08 - Testing using real traffic
- H04W 36/32 - Reselection being triggered by specific parameters by location or mobility data, e.g. speed data
- H04W 72/02 - Selection of wireless resources by user or terminal
- H04W 84/18 - Self-organising networks, e.g. ad hoc networks or sensor networks
- H04W 4/029 - Location-based management or tracking services
- H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
- H01Q 1/32 - Adaptation for use in or on road or rail vehicles
- G01C 21/28 - Navigation; Navigational instruments not provided for in groups specially adapted for navigation in a road network with correlation of data from several navigational instruments
|
41.
|
VEHICLE TRACTION MAP FOR AUTONOMOUS VEHICLES
Document Number |
03006661 |
Status |
Pending |
Filing Date |
2016-12-12 |
Open to Public Date |
2017-06-15 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Rander, Peter
- Bradley, David Mcallister
- Wood, Matthew
- Vandenberg, Dirk
|
Abstract
There is provided a traction determination system for use with autonomous vehicles. In some aspects, vehicles are equipped with resources for detecting a traction value of a road surface and transmit traction information to a network service. The vehicle may perform a variety of operations upon determining a traction value of a road surface. Also disclosed is a method of operating a vehicle, the method comprising: determining a traction value for a surface of a road segment, the traction value being correlative to a coefficient of friction; associating the traction value with a location of the surface; and storing the traction value in association with location data representing the location of the surface.
IPC Classes ?
- B60W 40/068 - Road friction coefficient
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- B60W 40/10 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to vehicle motion
|
42.
|
OPTIMIZING COMMUNICATION FOR AUTOMATED VEHICLES
Document Number |
03187447 |
Status |
In Force |
Filing Date |
2016-12-08 |
Open to Public Date |
2017-06-15 |
Grant Date |
2023-09-05 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Ross, William
- Aitken, Michael
|
Abstract
A backend system for a fleet of autonomous vehicles (AVs) for a given region can store a spectrum heat map indicating network coverage strength for a plurality of network types sourced at base stations located throughout the given region. The backend system can dynamically receive network quality data from the plurality of AVs traveling throughout the given region, and dynamically update the spectrum heat map based on the received network quality data.
IPC Classes ?
- H04W 48/20 - Selecting an access point
- H04W 48/16 - Discovering; Processing access restriction or access information
- H04W 4/40 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
|
43.
|
OPTIMIZING COMMUNICATION FOR AUTOMATED VEHICLES
Document Number |
03206651 |
Status |
In Force |
Filing Date |
2016-12-08 |
Open to Public Date |
2017-06-15 |
Grant Date |
2024-02-13 |
Owner |
UATC, LLC (USA)
|
Inventor |
- Ross, William
- Aitken, Michael
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Abstract
A backend system for a fleet of autonomous vehicles (AVs) for a given region can store a spectrum heat map indicating network coverage strength for a plurality of network types sourced at base stations located throughout the given region. The backend system can dynamically receive network quality data from the plurality of AVs traveling throughout the given region, and dynamically update the spectrum heat map based on the received network quality data.
IPC Classes ?
- H04W 40/22 - Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point
- H04W 76/14 - Direct-mode setup
- B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
- G08G 1/0968 - Systems involving transmission of navigation instructions to the vehicle
- H01Q 1/00 - ANTENNAS, i.e. RADIO AERIALS - Details of, or arrangements associated with, antennas
- H01Q 1/32 - Adaptation for use in or on road or rail vehicles
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44.
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LIDAR SCANNER CALIBRATION
Document Number |
02931055 |
Status |
In Force |
Filing Date |
2014-11-21 |
Open to Public Date |
2015-05-28 |
Grant Date |
2022-07-12 |
Owner |
UATC, LLC (USA)
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Inventor |
- Schwarz, Brent S.
- Haslim, James A.
- Iturraran, Nicholas M.
- Karasoff, Michael D.
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Abstract
A LiDAR can include a laser, an avalanche photodiode, a splitter, and a processor. The laser can be configured to emit a narrow electromagnetic pulse. The avalanche photodiode can be configured to receive one or more electromagnetic pulses and output a response signal in response to said pulses and can also be positioned to receive at least one reflected pulse, reflected by an object external from the LiDAR sensor and caused by the laser. The avalanche photodiode can also have a bias voltage applied to it affecting the response signal. The splitter can be positioned to receive the narrow electromagnetic pulse and split it into at least one external pulse directed toward the object external from the LiDAR sensor and at least one calibration pulse directed toward the photodiode. Further, the processor can be configured to adjust the bias voltage.
IPC Classes ?
- G01S 7/497 - Means for monitoring or calibrating
- G01S 7/4861 - Circuits for detection, sampling, integration or read-out
- G01S 7/486 - Receivers
- H01L 31/107 - Devices sensitive to infrared, visible or ultraviolet radiation characterised by only one potential barrier or surface barrier the potential barrier working in avalanche mode, e.g. avalanche photodiode
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45.
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METHODS, SYSTEMS, AND APPARATUS FOR MULTI-SENSORY STEREO VISION FOR ROBOTICS
Document Number |
02902430 |
Status |
In Force |
Filing Date |
2014-03-14 |
Open to Public Date |
2014-09-25 |
Grant Date |
2020-09-01 |
Owner |
UATC, LLC (USA)
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Inventor |
- Osterwood, Christopher Charles
- Strother, Daniel Leland
- Larose, David Arthur
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Abstract
Embodiments of the present invention include multi-sensory stereo vision sensors suitable for use in robotics, navigation, machine vision, manufacturing, and other applications. In some cases, a sensor includes a stereo camera that produces image data for use in generating disparity maps to determine the positions of objects in the scene and/or the position of the sensor itself. The stereo sensor may include image sensors that are fastened to a unitary frame to prevent undesired drift and a thermal pad that wicks heat away from a processor. The processor may provide an efficient means to directly compute stereo disparity maps onboard the sensor. A sensor can also include a laser rangefinder that provides range data suitable for calibrating the stereo camera and for improving its accuracy in certain environments. In some cases, the laser is coupled to a spindle, which in turn is driven by a gear-train through a slipping clutch.
IPC Classes ?
- G06T 7/70 - Determining position or orientation of objects or cameras
- G06T 7/593 - Depth or shape recovery from multiple images from stereo images
- H04N 13/128 - Adjusting depth or disparity
- H04N 13/239 - Image signal generators using stereoscopic image cameras using two 2D image sensors having a relative position equal to or related to the interocular distance
- H04N 13/246 - Calibration of cameras
- B25J 19/02 - Sensing devices
- G01B 11/00 - Measuring arrangements characterised by the use of optical techniques
- G01B 11/27 - Measuring arrangements characterised by the use of optical techniques for testing the alignment of axes for testing the alignment of axes
- G01D 11/24 - Housings
- G01M 11/02 - Testing optical properties
- G01S 7/497 - Means for monitoring or calibrating
- G01S 17/08 - Systems determining position data of a target for measuring distance only
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