Abstract: A component of a robotic system, including: processor circuitry; and a non-transitory computer-readable storage medium including instructions that, when executed by the processor circuitry, cause the processor circuitry to: train a neuro-capability map plugin, which is a continuous or semi-continuous resolution neural network component encoded with kinematic capability attributes with respect to an action to be performed by a robot in a workspace; and publish the neuro-capability map plugin to a robotic skills repository where it is obtainable by robotic controller circuitry for embedding within a neural network usable perform one or more inferences to control the robot to perform the action.

Abstract: A safety system for a vehicle may include one or more processors configured to determine, based on a friction prediction model, one or more predictive friction coefficients between the ground and one or more tires of the ground vehicle using first ground condition data and second ground condition data. The first ground condition data represent conditions of the ground at or near the position of the ground vehicle, and the second ground condition data represent conditions of the ground in front of the ground vehicle with respect to a driving direction of the ground vehicle. The one or more processors are further configured to determine driving conditions of the ground vehicle using the determined one or more predictive friction coefficients.

Abstract: An Autonomous Vehicle (AV) system, including: a tracking subsystem configured to detect and track relative positioning of another vehicle that is behind or lateral to an AV configured to comply with a safety driving model, and to check a safety driving model compliance status of the other vehicle; and a risk reduction subsystem configured to plan, based on the safety driving model compliance status of the other vehicle, an AV action, wherein if the safety driving model compliance status of the other vehicle is unknown or is known to be non-compliant, the AV action is administration of a safety driving model compliance test to the other vehicle, or is a maneuver by the AV to reduce risk of collision with a leading vehicle positioned in front of the AV.

Abstract: Systems, apparatuses and methods may provide for technology that adjusts, via a short-term subsystem, a communications parameter for one or more of wireless communication devices based on data from one or more of a plurality of sensors. The technology may also determine, via a neural network, a prediction of future performance of the wireless network based on a state of the network environment, wherein the state of the network environment includes information from the short-term subsystem and location information about the wireless communication devices and other objects in the environment, and determine a change in network configuration to improve a quality of communications in the wireless network based on the prediction of future performance of the wireless network. The technology may further generate generic path loss models based on time-stamped RSSI maps and record a sequence of events that cause a significant drop in RSSI to determine a change in network configuration.

Abstract: Systems, apparatuses and methods may provide for origination camera technology that generates a cell representation of a local space associated with an origination camera in a multicast domain, predicts that an object in the local space will exit the local space and enter one or more adjacent spaces associated with additional cameras in the multicast domain, and sends the cell representation and a trajectory of the object to the additional cameras before the object exits the local space. Additionally, transition camera technology may generate a leader election message based on a multicasted trajectory of an object and a predicted trajectory of the object, send the leader election message from a transition camera to one or more additional cameras in a multicast domain, and track the object in the local space in response to a leader notification message.

Abstract: A safety system for a vehicle may include one or more processors configured to determine, based on a friction prediction model, one or more predictive friction coefficients between the ground and one or more tires of the ground vehicle using first ground condition data and second ground condition data. The first ground condition data represent conditions of the ground at or near the position of the ground vehicle, and the second ground condition data represent conditions of the ground in front of the ground vehicle with respect to a driving direction of the ground vehicle. The one or more processors are further configured to determine driving conditions of the ground vehicle using the determined one or more predictive friction coefficients.

Abstract: Systems, apparatuses and methods may provide for technology that adjusts, via a short-term subsystem, a communications parameter for one or more of wireless communication devices based on data from one or more of a plurality of sensors. The technology may also determine, via a neural network, a prediction of future performance of the wireless network based on a state of the network environment, wherein the state of the network environment includes information from the short-term subsystem and location information about the wireless communication devices and other objects in the environment, and determine a change in network configuration to improve a quality of communications in the wireless network based on the prediction of future performance of the wireless network. The technology may further generate generic path loss models based on time-stamped RSSI maps and record a sequence of events that cause a significant drop in RSSI to determine a change in network configuration.

Abstract: Systems, apparatuses and methods may provide for technology that detects an unidentified individual at a first location along a trajectory in a scene based on a video feed of the scene, wherein the video feed is to be associated with a stationary camera, and selects a non-stationary camera from a plurality of non-stationary cameras based on the trajectory and one or more settings of the selected non-stationary camera. The technology may also automatically instruct the selected non-stationary camera to adjust at least one of the one or more settings, capture a face of the individual at a second location along the trajectory, and identify the unidentified individual based on the captured face of the unidentified individual.

Abstract: In an autonomous vehicle system, data received from one or more autonomous vehicles (AVs) can be aggregated to generate aggregated data. From this aggregated data, a vector-field map can be generated that includes a plurality of cells. Each of the cells can include a corresponding vector. The vector field map can be analyzed to identify one or more vectors of the plurality of cells that exceed one or more predetermined threshold values. The analysis can include a magnitude analysis and/or a frequency analysis. Based on the analysis, traffic and/or road conditions can be determined, which can provide prior knowledge about the driving behavior of other vehicles. Advantageously, aspects of the disclosure improve predictive motion models and enhance navigation algorithms.

Abstract: A safety system for a vehicle may include one or more processors configured to determine, based on a friction prediction model, one or more predictive friction coefficients between the ground and one or more tires of the ground vehicle using first ground condition data and second ground condition data. The first ground condition data represent conditions of the ground at or near the position of the ground vehicle, and the second ground condition data represent conditions of the ground in front of the ground vehicle with respect to a driving direction of the ground vehicle. The one or more processors are further configured to determine driving conditions of the ground vehicle using the determined one or more predictive friction coefficients.

Abstract: System and techniques for vehicle occupant monitoring are described herein. Sensor data, that includes visual image data, is obtained from a sensor array of the vehicle. An object carried by the vehicle is detected from the visual image data. A safety event for the vehicle may be identified based on the object detection and an operational element of the vehicle is altered in response to detecting the safety event.

Abstract: Methods and apparatus to train models for program synthesis are disclosed. A disclosed example apparatus includes at least one memory, instructions, and processor circuitry. The processor circuitry is to execute the instructions to sample pairs of programs, the pairs of programs including first programs and second programs, the first programs including natural language descriptions and second programs, calculate program similarity scores corresponding to the pairs of programs, and train a model based on entries corresponding to ones of the pairs of programs, at least one of the entries including a corresponding one of the natural language descriptions with a paired one of the second programs, and a corresponding one of the program similarity scores.

Abstract: Systems, apparatuses and methods may provide for origination camera technology that extracts data from multimodal sensor signals associated with a scene and generates a five-dimensional (5D) representation of the scene, wherein the 5D representation includes a three-dimensional (3D) visual representation, a one-dimensional (1D) temporal representation, and a 1D branch representation. The technology may also store the 5D representation as a set of abstract descriptors.

Abstract: Techniques are disclosed to realize a self-adaptive multiresolution digital plate (SAMDP) system that facilitates sharing of vehicle state information via a dynamically generated binary two-dimensional multispectral pattern. The binary 2D multispectral pattern adjusts its resolution to adapt to the visual perception process while communicating vehicle state information without relying on wireless communications (i.e. V2V, V2X, etc.). The techniques as described herein leverage the use of a multichannel spectral means that helps lower the error present in sensing and representation models used by automated driving systems.

Abstract: A robotic manipulation planning system, including at least one processor; and a non-transitory computer-readable storage medium including instructions that, when executed by the at least one processor, cause the at least one processor to: process perception data to detect known, familiar, and unknown objects to generate manipulation candidates; filter manipulation candidates against constraints to reduce the manipulation candidates; and determine quality metrics for the reduced manipulation candidates using a soft-body simulation technique.

Abstract: Systems, apparatuses and methods may provide for origination camera technology that generates a cell representation of a local space associated with an origination camera in a multicast domain, predicts that an object in the local space will exit the local space and enter one or more adjacent spaces associated with additional cameras in the multicast domain, and sends the cell representation and a trajectory of the object to the additional cameras before the object exits the local space. Additionally, transition camera technology may generate a leader election message based on a multicasted trajectory of an object and a predicted trajectory of the object, send the leader election message from a transition camera to one or more additional cameras in a multicast domain, and track the object in the local space in response to a leader notification message.

Abstract: Systems, apparatuses and methods may provide for origination camera technology that extracts data from multimodal sensor signals associated with a scene and generates a five-dimensional (5D) representation of the scene, wherein the 5D representation includes a three-dimensional (3D) visual representation, a one-dimensional (1D) temporal representation, and a 1D branch representation. The technology may also store the 5D representation as a set of abstract descriptors.

Abstract: Systems, apparatuses and methods may provide for technology that adjusts, via a short-term subsystem, a communications parameter for one or more of wireless communication devices based on data from one or more of a plurality of sensors. The technology may also determine, via a neural network, a prediction of future performance of the wireless network based on a state of the network environment, wherein the state of the network environment includes information from the short-term subsystem and location information about the wireless communication devices and other objects in the environment, and determine a change in network configuration to improve a quality of communications in the wireless network based on the prediction of future performance of the wireless network. The technology may further generate generic path loss models based on time-stamped RSSI maps and record a sequence of events that cause a significant drop in RSSI to determine a change in network configuration.

Abstract: Systems, apparatuses and methods may provide for technology that detects an unidentified individual at a first location along a trajectory in a scene based on a video feed of the scene, wherein the video feed is to be associated with a stationary camera, and selects a non-stationary camera from a plurality of non-stationary cameras based on the trajectory and one or more settings of the selected non-stationary camera. The technology may also automatically instruct the selected non-stationary camera to adjust at least one of the one or more settings, capture a face of the individual at a second location along the trajectory, and identify the unidentified individual based on the captured face of the unidentified individual.

Abstract: A safety system for a vehicle may include one or more processors configured to determine, based on a friction prediction model, one or more predictive friction coefficients between the ground and one or more tires of the ground vehicle using first ground condition data and second ground condition data. The first ground condition data represent conditions of the ground at or near the position of the ground vehicle, and the second ground condition data represent conditions of the ground in front of the ground vehicle with respect to a driving direction of the ground vehicle. The one or more processors are further configured to determine driving conditions of the ground vehicle using the determined one or more predictive friction coefficients.