Abstract: A method for generating a dense light detection and ranging (LiDAR) representation by a vision system includes receiving, at a sparse depth network, one or more sparse representations of an environment. The method also includes generating a depth estimate of the environment depicted in an image captured by an image capturing sensor. The method further includes generating, via the sparse depth network, one or more sparse depth estimates based on receiving the one or more sparse representations. The method also includes fusing the depth estimate and the one or more sparse depth estimates to generate a dense depth estimate. The method further includes generating the dense LiDAR representation based on the dense depth estimate and controlling an action of the vehicle based on identifying a three-dimensional object in the dense LiDAR representation.

Abstract: A system for predicting a drying protocol for drying a film containing a polymer includes a processor, and a memory communicably coupled to the processor. The memory includes and stores machine-readable instructions that, when executed by the processor, cause the processor to analyze a captured image of a film containing the polymer dried per a first drying protocol and including a defect, identify and classify the defect, and predict, based at least in part on the first drying protocol and the classified defect, a second drying protocol different than the first drying protocol for drying another film containing the polymer.

Abstract: The disclosure generally describes a system and method for determining a preferred steering wheel rate in autonomous and semi-autonomous driving systems that includes measuring a torque applied to the steering wheel by a driver during an autonomous driving mode, measuring the steering wheel position, measuring the steering wheel rate of rotation, wherein the steering position and rate of rotation are measured at the time when the torque was applied to the steering wheel, determining a preferred steering wheel rate of rotation, and adjusting the steering wheel rate of rotation during an autonomous driving maneuver to include the preferred steering wheel rate.

Abstract: Arrangements described herein can facilitate the development of autonomous driving applications by enabling a user to modify existing parameters and/or define new parameters in scenario files and/or to create driving evaluation tools. A first user interface based on a schema can be generated. A first input, such as a new parameter or a modification to an existing parameter defined by a schema, can be provided on the first user interface. A second user interface can be generated using the first input provided on the first user interface. The second user interface can include the new parameter or the modification to the existing parameter. A second input relating to the new parameter or the modification to the existing parameter can be received on the second user interface. Valid data can be generated based on the second input and that conforms with the schema.

Abstract: Systems, methods, and other embodiments described herein relate to a multi-task model that integrates recurrent models to improve handling of multi-sweep inputs. In one embodiment, a method includes acquiring sensor data from multiple modalities. The method includes separately encoding respective segments of the sensor data according to an associated one of the different modalities to form encoded features using separate encoders of a network. The method includes accumulating, in a detector, sparse features associated with sparse sensor inputs of the multiple modalities to densify the sparse features into dense features. The method includes providing observations according to the encoded features and the sparse features using the network.

Abstract: A system for coordinating use of different motion prediction models to predict a location of a mobile robot at a future point in time can include a first motion prediction model module, a second motion prediction model module, a decision module, and an actuator module. The first motion prediction model module can determine, operating a first motion prediction model, a first prediction of a location of a mobile robot at a future point in time. The second motion prediction model module can determine, operating a second motion prediction model, a second prediction of the location of the mobile robot at the future point in time. The decision module can determine an existence of a condition. The actuator module can cause, based on a determination of the existence of the condition, the mobile robot to move based on one or more of the first prediction or the second prediction.

Abstract: Systems, methods, and other embodiments described herein relate to determining a type and an issue time of a vehicle control command based on an estimated realization delay. In one embodiment, a method includes identifying a first realization delay associated with a first control command and identifying a second realization delay associated with a second control command. The second control command is issued after the first control command is issued. The method includes issuing the first control command at an issue time that is based on the first realization delay and the second realization delay, and realizing the first control command on a vehicle.

Abstract: Systems and methods are described for optimizing bounding boxes generated using point cloud information. In one example, a method for optimizing the bounding box includes the step of using an iterative closet point (ICP) algorithm to transform the bounding box using a transformation. The point cloud acts as the reference for the ICP algorithm, while the bounding box acts as the source for the ICP algorithm.

Abstract: A method for fitting an odometry noise model of a vehicle is described. The method includes collecting multiple passes of sensor measurements from motion sensors of the vehicle to measure a motion sensor noise during a testing operation of the vehicle. The method also includes determining an estimated standard deviation of the motion sensor noise measured during the testing operation of the vehicle. The method further includes determining the odometry noise model of the vehicle according to the estimated standard deviation of the motion sensor noise measured during the testing operation of the vehicle. The method also includes compensating, using the odometry noise model, the motion sensor noise during normal operation of the vehicle.

Abstract: Systems and methods are provided for lane biasing, e.g., positioning a vehicle within a current lane of travel. Lane biasing can be dependent on learned driver behaviors or other factors that may impact lane biasing, e.g., weather conditions, traffic conditions, and so on (which may also be learned). Lane biasing may result in a vehicle traveling, e.g., off the center-line of a current lane of travel, and is distinguished from conventional lane keep assist systems that merely position a vehicle in the center of a current lane of travel by default.

Abstract: A method performed by an autonomous vehicle includes identifying a condition preventing the autonomous vehicle from proceeding along an intended route. The method also includes prompting a passenger of the autonomous vehicle to interact with a driver of a first vehicle in response to identifying the condition. The method further includes receiving, from the passenger, an input at an interface of the autonomous vehicle indicating a successful interaction or an unsuccessful interaction with the driver. The method also includes controlling the autonomous vehicle to proceed along the intended route based on the input indicating the successful interaction with the driver.

Abstract: Systems and methods for controlling a vehicle using operational constraints, including friction estimates are disclosed. Friction estimation include estimating a tire-road coefficient of friction using bins and envelopes. Bounding envelopes are configured to ensure that stability of the vehicle is maintained. The friction estimate is used to define the bounding envelopes. Further, the bounding envelopes are received as feedback into the friction estimation, itself. Based on the bounding envelope, the friction estimation can be adjusted. Then, the adjusted friction estimation can be fed back to reshape the bounding envelopes. Multiple bins can be used to evaluate an operating range of friction. Each bin can be used to compare actual vehicle dynamics with expected dynamics based on the estimation using the range assigned to that bin. Multiple bins and multiple controllers can run in parallel to re-estimate friction considering the vehicle dynamics over time.

Abstract: A method for depth estimation performed by a depth estimation system associated with an agent includes determining a first depth of a first image and a second depth of a second image, the first image and the second image being captured by a sensor associated with the agent. The method also includes generating a first 3D image of the first image based on the first depth, a first pose associated with the sensor, and the second image. The method further includes generating a warped depth image based on transforming the first depth in accordance with the first pose. The method also includes updating the first pose based on a second pose associated with the warped depth image and the second depth, and updating the first 3D image based on the updated first pose. The method further includes controlling an action of the agent based on the updated first 3D image.

Abstract: A system is provided for implementing trajectory analysis entry controls. A trajectory analysis entry control system is implemented in a vehicle, and supports remote and automatic entry control functions for the vehicle. For example the system triggers various automatic entry controls functions, such as remotely unlocking doors and/or a trunk of a vehicle, by tracking and analyzing a user's trajectory of movement while they are approaching the vehicle. A system includes a user identification device to identify whether a user is authorized to access the vehicle, such as a driver. The system also includes a trajectory tracking device that determines a trajectory of the user with respect to the vehicle. As the user's trajectory is determined to be approaching the vehicle, the trajectory tracking device further determines which entry point of the vehicle the user is approaching and automatically engages an automatic unlocking of that access point of the vehicle.

Abstract: A system for producing a trajectory from a diverse set of possible movements can include a processor and a memory. The memory can store a possible movement production module and a trajectory production module. The possible movement production module can include instructions that cause the processor to: (1) produce a set of possible movements of a mobile robot with respect to a challenge, (2) determine a measure of diversity between a first possible movement and a second possible movement, and (3) produce a subset. Measures of diversity associated with possible movements included in the subset can be larger than measures of diversity associated with possible movements excluded from the subset. The trajectory production module can include instructions that cause the processor to: (1) produce trajectories associated with the possible movements included in the subset and (2) cause the mobile robot to move according to one of the trajectories.

Abstract: Systems and methods are provided for variable actuation and release of a vehicle's brake hold mechanism/function. A brake hold device may be implemented as a “tuner” or controller that can connect to and override, e.g., the default functionality of an existing brake hold mechanism of a vehicle. Delays in exiting a brake hold state, repetitive actuation of an accelerator to exit a brake hold state, and other shortcomings associated with the conventional operation of brake hold mechanisms may be avoided by taking into account relevant vehicle operating conditions or environmental/road/traffic conditions.

Abstract: The disclosure generally describes a system for monitoring a storage compartment of a vehicle comprising a first sensor configured to detect a loading or unloading event, a second sensor configured to capture data regarding one or more items within the storage compartment of the vehicle, wherein the second sensor captures video data of the one or more items within the storage compartment of the vehicle in response to the first sensor detecting a loading or unloading event, and a virtual imaging system configured to classify each item in the storage compartment, generate a virtual replication of each item within the storage compartment, and transmit the virtual replication to a user device.

Abstract: System, methods, and other embodiments described herein relate to improving the detection of traffic lights associated with a driving lane using a camera instead of map data. In one embodiment, a method includes estimating, from an image using a first model, depth and orientation information of traffic lights relative to a driving lane of a vehicle. The method also includes computing, using a second model, relevancy scores for the traffic lights according to geometric inferences between the depth and the orientation information. The method also includes assigning, using the second model, a primary relevancy score for a light of the traffic lights associated with the driving lane according to the depth and the orientation information. The method also includes executing a control task by the vehicle according to the primary relevancy score and a state confidence, computed by the first model, for the light.

Abstract: Systems and methods for optimizing the loading or unloading of cargo in a cargo area is provided. Friction-reducing elements, such as rails, may be disposed atop a surface of the cargo area. The friction-reducing elements vibrate pursuant to the application of vibrational energy generated by one or more vibration actuators operatively connected, directly or indirectly, to the friction-reducing elements. The application of vibrational energy reduces the time that cargo contacts the friction-reducing elements, which in turn, reduces the amount of friction applied to the cargo, easing the burden of loading/unloading the cargo.

Abstract: In accordance with one embodiment of the present disclosure, a sensor system includes a sensing surface and an array of pressure sensors arranged on the sensing surface. The array of pressure sensors includes at least one pressure sensor is parallel to the sensing surface, at least one pressure sensor is angled between parallel and perpendicular to the sensing surface, and at least one pressure sensor is perpendicular to the sensing surface. The pressure sensors are micro electro mechanical system (MEMS) barometric pressure sensors.