Patents Assigned to UATC, LLC
  • Patent number: 11468575
    Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices associated with motion flow estimation are provided. For example, scene data including representations of an environment over a first set of time intervals can be accessed. Extracted visual cues can be generated based on the representations and machine-learned feature extraction models. At least one of the machine-learned feature extraction models can be configured to generate a portion of the extracted visual cues based on a first set of the representations of the environment from a first perspective and a second set of the representations of the environment from a second perspective. The extracted visual cues can be encoded using energy functions. Three-dimensional motion estimates of object instances at time intervals subsequent to the first set of time intervals can be determined based on the energy functions and machine-learned inference models.
    Type: Grant
    Filed: August 5, 2019
    Date of Patent: October 11, 2022
    Assignee: UATC, LLC
    Inventors: Raquel Urtasun, Wei-Chiu Ma, Shenlong Wang, Yuwen Xiong, Rui Hu
  • Patent number: 11467580
    Abstract: Systems and methods for detecting a surprise or unexpected movement of an actor with respect to an autonomous vehicle are provided. An example computer-implemented method can include, for a first compute cycle, obtaining motion forecast data based on first sensor data collected with respect to an actor relative to an autonomous vehicle; and determining, based on the motion forecast data, failsafe region data representing an unexpected path or area where a likelihood of the actor following the unexpected path or entering the unexpected area is below a threshold. For a second compute cycle after the first compute cycle, the method can include obtaining second sensor data; determining, based on the second sensor data and the failsafe region data, that the actor has followed the unexpected path or entered the unexpected area; and in response to such determination, determining a deviation for controlling a movement of the autonomous vehicle.
    Type: Grant
    Filed: March 6, 2020
    Date of Patent: October 11, 2022
    Assignee: UATC, LLC
    Inventors: Galen Clark Haynes, Neil Traft, Skanda Shirdhar, Charles R. Hogg, III
  • Patent number: 11465630
    Abstract: Systems and methods are provided for generating data indicative of a friction associated with a driving surface, and for using the friction data in association with one or more vehicles. In one example, a computing system can detect a stop associated with a vehicle and initiate a steering action of the vehicle during the stop. The steering action is associated with movement of at least one tire of the vehicle relative to a driving surface. The computing system can obtain operational data associated with the steering action during the stop of the vehicle. The computing system can determine a friction associated with the driving surface based at least in part on the operational data associated with the steering action. The computing system can generate data indicative of the friction associated with the driving surface.
    Type: Grant
    Filed: September 14, 2018
    Date of Patent: October 11, 2022
    Assignee: UATC, LLC
    Inventors: Scott C. Poeppel, Mats Jonasson
  • Patent number: 11462022
    Abstract: A traffic signal analysis system for an autonomous vehicle (AV) can receive image data from one or more cameras, the image data including an upcoming traffic signaling system located at an intersection. The system can determine an action for the AV through the intersection and access a matching signal map specific to the upcoming traffic signaling system. Using the matching signal map, the system can generate a signal template for the upcoming traffic signaling system and determine a first subset and a second subset of the plurality of traffic signal faces that apply to the action. The system can dynamically analyze the first subset and the second subset to determine a state of the upcoming traffic signaling system for the action, and generate an output for the AV indicating the state of the upcoming traffic signaling system for the action.
    Type: Grant
    Filed: June 5, 2020
    Date of Patent: October 4, 2022
    Assignee: UATC, LLC
    Inventors: Carl Wellington, Colin Green, Adam Milstein
  • Patent number: 11461963
    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 geometry model can predict one or more adjusted depths 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.
    Type: Grant
    Filed: September 11, 2019
    Date of Patent: October 4, 2022
    Assignee: UATC, LLC
    Inventors: Sivabalan Manivasagam, Shenlong Wang, Wei-Chiu Ma, Raquel Urtasun
  • Patent number: 11461583
    Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices associated with object localization and generation of compressed feature representations are provided. For example, a computing system can access training data including a source feature representation and a target feature representation. An encoded target feature representation can be generated based on the target feature representation and a machine-learned encoding model. A binarized target feature representation can be generated based on the encoded target feature representation and lossless binarization operations. A reconstructed target feature representation can be generated based on the binarized target feature representation and a machine-learned decoding model. A matching score for the source feature representation and the reconstructed target feature representation can be determined. A loss associated with the matching score can be determined.
    Type: Grant
    Filed: October 10, 2019
    Date of Patent: October 4, 2022
    Assignee: UATC, LLC
    Inventors: Raquel Urtasun, Xinkai Wei, Ioan Andrei Barsan, Julieta Martinez Covarrubias, Shenlong Wang
  • Patent number: 11458997
    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.
    Type: Grant
    Filed: June 5, 2020
    Date of Patent: October 4, 2022
    Assignee: UATC, LLC
    Inventors: Sean Hyde, Jose Francisco Molinari, Stephen Luke Thomas
  • Patent number: 11454975
    Abstract: Systems and methods are provided for detecting objects of interest. A computing system can input sensor data to one or more first machine-learned models associated with detecting objects external to an autonomous vehicle. The computing system can obtain as an output of the first machine-learned models, data indicative of one or more detected objects. The computing system can determine data indicative of at least one uncertainty associated with the one or more detected objects and input the data indicative of the one or more detected objects and the data indicative of the at least one uncertainty to one or more second machine-learned models. The computing system can obtain as an output of the second machine-learned models, data indicative of at least one prediction associated with the one or more detected objects. The at least one prediction can be based at least in part on the detected objects and the uncertainty.
    Type: Grant
    Filed: July 24, 2018
    Date of Patent: September 27, 2022
    Assignee: UATC, LLC
    Inventors: Cole Christian Gulino, Alexander Rashid Ansari
  • Patent number: 11454973
    Abstract: A method for receiving autonomous vehicle (AV) driving path data associated with a driving path in a roadway of a geographic location. The driving path data associated with a trajectory for an AV in a roadway and trajectory points in a trajectory of the driving path in the roadway for determining at least one feature of the roadway positioned a lateral distance from a first trajectory of the one or more trajectories of the driving path of an AV based on the map data. The method includes receiving map data associated with a map of a geographic location, determining a driving path for an AV in a roadway, generating driving path information based on a trajectory point in a trajectory of the driving path, and providing driving path data associated with the driving path to an AV for controlling the AV on the roadway.
    Type: Grant
    Filed: September 10, 2020
    Date of Patent: September 27, 2022
    Assignee: UATC, LLC
    Inventors: Adam Henry Polk Milstein, Donald Jason Burnette, Lisa Christine Weitekamp, Bryan John Nagy, Eric Michael Perko
  • Patent number: 11447055
    Abstract: Systems and methods are directed to automated delivery systems. In one example, a vehicle is provided including a drive system, a passenger cabin; and a delivery service pod provided relative to the passenger cabin. The delivery service pod includes an access unit configured to allow for loading and unloading of a plurality of delivery crates into the delivery service pod. The delivery service pod further includes a conveyor unit comprising multiple delivery crate holding positions, the delivery crate holding positions being defined by neighboring sidewalls spaced apart within the delivery service pod such that a respective delivery crate of the plurality of delivery crates can be positioned between neighboring sidewalls, wherein the conveyor unit is configured to be rotated to align each of the delivery crate holding positions with the access unit.
    Type: Grant
    Filed: July 17, 2018
    Date of Patent: September 20, 2022
    Assignee: UATC, LLC
    Inventor: Daniel Adam Kanitz
  • Patent number: 11449713
    Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices associated with object localization and generation of compressed feature representations are provided. For example, a computing system can access training data including a target feature representation and a source feature representation. An attention feature representation can be generated based on the target feature representation and a machine-learned attention model. An attended target feature representation can be generated based on masking the target feature representation with the attention feature representation. A matching score for the source feature representation and the target feature representation can be determined. A loss associated with the matching score and a ground-truth matching score for the source feature representation and the target feature representation can be determined. Furthermore, parameters of the machine-learned attention model can be adjusted based on the loss.
    Type: Grant
    Filed: October 10, 2019
    Date of Patent: September 20, 2022
    Assignee: UATC, LLC
    Inventors: Raquel Urtasun, Xinkai Wei, Ioan Andrei Barsan, Julieta Martinez Covarrubias, Shenlong Wang
  • Patent number: 11441913
    Abstract: Various examples are directed to systems and methods for navigating an autonomous vehicle. Trip plan data may describe a plurality of candidate vehicle start points, a plurality of candidate waypoints, and a plurality of candidate vehicle end points. A plurality of candidate routes may be determined between an algorithm start point and an algorithm end point. Each candidate route of the plurality of candidate routes may include at least one of the plurality of candidate waypoints and at least one of the plurality of candidate vehicle end points. A best rate may be determined using the plurality of candidate routes. The best route may include a first candidate vehicle start point, a first candidate waypoint, and a first candidate vehicle end point. The autonomous vehicle may be controlled along the best route from the first candidate vehicle start point towards the first candidate vehicle end point.
    Type: Grant
    Filed: October 29, 2018
    Date of Patent: September 13, 2022
    Assignee: UATC, LLC
    Inventors: Bryan John Nagy, Xiaodong Zhang, Brett Bavar, Misna Sameer
  • Patent number: 11443148
    Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices for autonomous vehicle operation are provided. For example, a computing system can receive object data that includes portions of sensor data. The computing system can determine, in a first stage of a multiple stage classification using hardware components, one or more first stage characteristics of the portions of sensor data based on a first machine-learned model. In a second stage of the multiple stage classification, the computing system can determine second stage characteristics of the portions of sensor data based on a second machine-learned model. The computing system can generate an object output based on the first stage characteristics and the second stage characteristics. The object output can include indications associated with detection of objects in the portions of sensor data.
    Type: Grant
    Filed: August 31, 2020
    Date of Patent: September 13, 2022
    Assignee: UATC, LLC
    Inventors: Carlos Vallespi-Gonzalez, Joseph Lawrence Amato, George Totolos, Jr.
  • Patent number: 11441983
    Abstract: In one aspect, a method for conducting a drop test of an article with one or more target parameters can include dropping the article and a drop carriage of a drop tower from an initial height with respect to a base of the drop tower for an initial drop test. The article can be coupled to the drop carriage. The method can include detecting accelerometer data with respect to the article for an initial impact between the drop carriage and the base of the drop tower; determining a constant energy balance curve; determining, based on the constant energy balance curve and a target pulse duration, a target complex stiffness and/or a target total weight; adjusting, based on the target complex stiffness or the target total weight, the complex stiffness and/or the total weight for a subsequent drop test; and conducting the subsequent drop test.
    Type: Grant
    Filed: August 12, 2020
    Date of Patent: September 13, 2022
    Assignee: UATC, LLC
    Inventors: Jonathan Miller, Paul Kevin Smith, Mark Vincent Brancale
  • Patent number: 11440490
    Abstract: Systems and methods for controlling autonomous vehicles are provided. In one example embodiment, a computing system can obtain data indicative of a service assignment associated with an autonomous vehicle. The service assignment is indicative of a destination location. The computing system can determine a checklist associated with the destination location. The computing system can provide, for display via a display device, data indicative of a user interface. The user interface can present the checklist associated with the destination location. The computing system can obtain data indicative of user input associated with the checklist. The computing system can determine that the checklist has been completed based at least in part on the user input associated with the checklist. The computing system can, in response to determining that the checklist has been completed, cause the autonomous vehicle to initiate a motion control to travel to the destination location.
    Type: Grant
    Filed: October 30, 2018
    Date of Patent: September 13, 2022
    Assignee: UATC, LLC
    Inventors: Min Kyu Park, Christopher Matthew D'Eramo
  • Patent number: 11440440
    Abstract: The present disclosure is directed to a modular autonomous-vehicle interior. In particular, an autonomous vehicle can comprise an interior comprising a plurality of different and distinct regions. Each of the regions can comprise one or more mechanical interfaces associated therewith. The autonomous vehicle can also include, for each of one or more of the regions, at least one modular interior unit comprising an interior element and a base mechanically interfaced with the interior via the mechanical interface(s) associated with the region.
    Type: Grant
    Filed: October 30, 2018
    Date of Patent: September 13, 2022
    Assignee: UATC, LLC
    Inventors: Johad Husseini Ellis, Clifford Shaun Webb
  • Patent number: 11442459
    Abstract: Systems and methods for training machine-learned models are provided. A method can include receiving a rasterized image associated with a training object and generating a predicted trajectory of the training object by inputting the rasterized image into a first machine-learned model. The method can include converting the predicted trajectory into a rasterized trajectory that spatially corresponds to the rasterized image. The method can include utilizing a second machine-learned model to determine an accuracy of the predicted trajectory based on the rasterized trajectory. The method can include determining an overall loss for the first machine-learned model based on the accuracy of the predictive trajectory as determined by the second machine-learned model. The method can include training the first machine-learned model by minimizing the overall loss for the first machine-learned model.
    Type: Grant
    Filed: February 6, 2020
    Date of Patent: September 13, 2022
    Assignee: UATC, LLC
    Inventors: Henggang Cui, Junheng Wang, Sai Bhargav Yalamanchi, Mohana Prasad Sathya Moorthy, Fang-Chieh Chou, Nemanja Djuric
  • Patent number: 11435194
    Abstract: A georeferenced trajectory system for vehicles receives trajectory data generated by a plurality of vehicle sensors and scaffolds of previously generated maps and aligns geometry data for a geographic region and trajectory data from the received data from different map builds. A scaffold of a geographic region to be mapped during an initial map build is generated, and the trajectory data from respective map builds is aligned with the scaffold of previously generated maps to generate a map of the geographic region. The resulting map expands the coverage of the existing map such that old and new map data is in a common consistent reference frame whereby the map may be built incrementally by merging or expanding local scaffolds and filling in the merged or expanded scaffold while ensuring global consistency.
    Type: Grant
    Filed: January 28, 2020
    Date of Patent: September 6, 2022
    Assignee: UATC, LLC
    Inventors: David Prasser, Evan Herbst, Robert Zlot, Jennifer Joyce Padgett, Bryan John Nagy, Xiaodong Zhang, Michael Napoli, Adrian Rechy Romero
  • Patent number: 11435200
    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.
    Type: Grant
    Filed: January 24, 2020
    Date of Patent: September 6, 2022
    Assignee: UATC, LLC
    Inventors: Bryan John Nagy, Michael Voznesensky, Brent Goldman, Robert Michael S Dean, Jian Wen, Yanbo Zhao
  • Patent number: 11427223
    Abstract: Systems and methods are provided for generating data indicative of a friction associated with a driving surface, and for using friction data as part of controlling autonomous vehicle operations. In one example, a computing system can detect an event including at least one of an acceleration, a deceleration, or a stop associated with an autonomous vehicle and obtain, in response to detecting the event, operational data associated with the autonomous vehicle during the event. The computing system can determine, based at least in part on the operational data, data indicative of a friction associated with a surface upon which the autonomous vehicle is traveling during the event. The computing system can control the autonomous vehicle based at least in part on the data indicative of the friction associated with the surface.
    Type: Grant
    Filed: September 14, 2018
    Date of Patent: August 30, 2022
    Assignee: UATC, LLC
    Inventors: Scott C. Poeppel, Mats Jonasson