Abstract: A robot generates a cell grid (e.g., occupancy grid) representation of a geographic area. The occupancy grid may include a plurality of evenly sized cells, and each cell may be assigned an occupancy status, which can be used to indicate the location of obstacles present in the geographic area. Footprints for the robot corresponding to a plurality of robot orientations and joint states may be generated and stored in a look-up table. The robot may generate a planned path for the robot to navigate within the geographic area by generating a plurality of candidate paths, each candidate path comprising a plurality of candidate robot poses. For each candidate robot pose, the robot may query the look-up table for a corresponding robot footprint to determine if a collision will occur.

Abstract: A lift device includes multiple electrical components and a battery monitoring system. The battery monitoring system includes multiple batteries and a controller. The multiple batteries are configured to power the multiple electrical components. The controller is configured to obtain sensor data from the batteries. The controller is also configured to determine a state of charge of the batteries for open circuit conditions based on the sensor data. The controller is configured to determine a state of charge of the batteries for load conditions based on the sensor data. The controller is configured to determine a state of charge of the batteries for charging conditions based on the sensor data. The controller determines an overall state of charge of the batteries based on the state of charge for open circuit conditions, the state of charge of the batteries for load conditions, and the state of charge for charging conditions.

Abstract: A work machine control device includes a lift force detection unit, a control amount determination unit, and a command output unit. The lift force detection unit detects a lift force of the work machine. The control amount determination unit determines a control amount for the work machine based on a change amount of the detected lift force. The command output unit outputs, to an actuator driving the work machine, a control command according to the determined control amount. The control amount determination unit determines the control amount such that the control amount monotonically increases with respect to the lift force until a lift amount of the work machine reaches a predetermined threshold. A work vehicle includes the work machine control device, a vehicle body, a work machine supported by the vehicle body, and an actuator that drives the work machine.

Abstract: Methods and systems are provided for selectively disabling a stop-start function of a vehicle based on a predicted anxiety of a driver of the vehicle upon merging into transverse traffic. In one example, selectively disabling the stop-start function of a vehicle based on a predicted anxiety of the driver of the vehicle includes, when approaching an intersection having a first traffic pattern, disabling a stop-start function responsive to an estimated merging acceleration for the intersection exceeding a threshold acceleration rate of the vehicle.

Abstract: A system for dynamically adjusting a configuration of an intra-train communication network includes an electronic device and a computer-readable storage medium. The computer-readable storage medium has one or more programming instructions that, when executed, cause the electronic device to receive one or more parameters values associated with a train consist, determine whether a potentially adverse condition that would affect intra-train communication for the train consist is anticipated based on at least a portion of the received parameters, in response to determining that the potentially adverse condition is anticipated, identify one or more updated network parameter settings that will assist in maintaining intra-train communication of the train consist during an occurrence of the potentially adverse condition by executing a machine learning model, and implement the identified one or more updated network parameter settings.

Abstract: A shovel includes a lower traveling body, an upper swiveling body that is mounted on the lower traveling body so as to be able to swivel, a traveling actuator that drives the lower traveling body, and a control device that is provided in the upper swiveling body, wherein the control device operates the traveling actuator based on information about a target position.

Abstract: A mobile work machine includes a frame, a material loading system having a material receiving area configured to receive material and an actuator configured to control the material loading system to move the material receiving area relative to the frame, and a control system configured to receive an indication of a detected object, determine a location of the object relative to the material loading system, and generate a control signal that controls the mobile work machine based on the determined location.

Abstract: A system for estimating a trajectory of a vehicle includes vehicle state sensors detecting a state of movement of the vehicle and environment sensors monitoring an environment of the vehicle. A free space module determines a free space corridor based on the detected state of movement of the vehicle and the monitored environment of the vehicle. A goal point determination module determines at least one goal point for the trajectory to be estimated based on the free space corridor. A trajectory planning module estimates a reference trajectory based on the at least one goal point and calculates a deviation between an actual trajectory and the reference trajectory of the vehicle. A trajectory control module minimizes the deviation between the actual trajectory and the reference trajectory of the vehicle and outputs optimal control parameters for the movement of the vehicle based on the minimized deviation.

Abstract: In some examples, a dual-mode autonomous guided vehicle (AGV) is provided for docking a module in a fabrication bay. An example AGV may comprise a chassis for supporting the module on the AGV; drive means to transport the AGV under autonomous guidance, in a module transportation mode, to a specified location within the fabrication bay; a Cartesian x-y movement table to move the module under autonomous guidance, in a module docking mode, in an x- or y-docking direction, into a specific docking position; and a z-direction lift mechanism to move the module in a z-docking direction during the module docking mode.

Abstract: Aspects of the disclosed technology encompass solutions for automatically requesting a backup vehicle for passengers of an autonomous vehicle provisioned ride-hailing service. In some aspects, a process of the disclosed technology includes steps for collecting diagnostic data relating to at least one AV operation, and analyzing the diagnostic data to determine if the AV needs maintenance. Moreover, in response to a determination that the AV needs maintenance, the process can include steps for automatically requesting a backup service for a passenger of the AV. Systems and machine-readable media are also provided.

Abstract: Disclosed are systems and methods for autonomous vehicles and vehicles with automatic driver-assistance systems (ADAS) to automatically detect an imminent collision, determine whether the collision is avoidable or unavoidable, and plot a course minimizing the hazard using an artificial intelligence (AI) model. For example, a collision is avoidable if the vehicle can avoid it by steering, braking, and/or accelerating in a particular sequence. The AI model finds the best sequence for collision avoidance, and if that is not possible, it finds the best sequence for minimizing the harm. The harm is based on an estimated number of fatalities, injuries, and property damage predicted to be caused in the collision. The AI-based situation analysis and sequence selection are directly applicable to human-driven vehicles with an emergency-intervention ADAS system, as well as fully autonomous vehicles. With fast electronic reflexes and multi-sensor situation awareness, the AI model can save lives on the highway.

Abstract: Embodiments provide techniques, including systems and methods, for determining matches of requestors and providers based on a dynamic provider eligibility model. For example, a request matching model uses an estimated arrival time for a requestor and estimated travel times for available providers to a pickup location to determine eligible providers for matching to a ride request. The matching model determines those providers that are far enough away from the request location to allow the requestor time to arrive at the pickup location without matching providers that are too far away, causing delay for the requestor and lowering the efficiency of the system by taking provider system resources from other service areas and increasing provider downtime upon matching. Additionally, embodiments provide more efficient matching processing leading to fewer canceled matched requests, fewer requests for a successful match, and fewer system resources necessary to meet requestor demand.

Abstract: Described is a computer-implemented method which comprises receiving a plurality of images captured by at least one user device, wherein each image is associated with one of a corresponding plurality of geographic locations; determining a path between the plurality of geographic locations; determining a confidence indicator representative of whether the determined path corresponds to a demarked path, wherein determining the confidence indicator comprises determining a time of capture of each of the plurality of images; identifying the path as corresponding to a demarked route, based on the confidence indicator; and marking the plurality of images for display as a demarked route.

Abstract: A system that may include a first route circuit that may be configured to be coupled with a first route section and may be configured to generate a first location coded signal that is unique to the first route section responsive to a vehicle being located on or within the first route section. A second route circuit may be configured to be coupled with a second route section and configured to generate a second location coded signal that is unique to the second route section and that is different from the first location coded signal, the second route circuit configured to generate the second location coded signal responsive to the vehicle being located on or within the second route section. A controller may be configured to receive the first location coded signal and the second location coded signal and determine a location of the vehicle based on the first location coded signal or the second location coded signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for allowing vehicles access or egress from a dedicated roadway. In some implementations, a system includes a server, an interface, and sensors. The interface receives data from a railroad system that manages a railroad running parallel to a first roadway. The sensors are positioned in a location relative to the first and second roadway. Each sensor can detect vehicles on the second roadway. For each detected vehicle, each sensor can generate first sensor data based on the detected vehicle and the data received at the interface. Second sensor data can be generated based on activities on the first roadway. Observational data can be generated based on the first and second sensor data. An instruction can be determined to allow the detected vehicle access to the first roadway. The instruction can be transmitted to the detected vehicle.

Abstract: The present invention relates to method and system for controlling speed of vehicle by using GPS location, real-time traffic light status and machine learning techniques to recommend cruising speed to vehicle without stopping at the traffic lights. The method includes determining status of traffic lights located on route of traffic junctions and associated time period for status of traffic lights based on data received from sensors. The method includes broadcasting status of traffic lights and associated time period. The method includes calculating in real-time a recommended cruising speed of the vehicle based on GPS location associated with vehicle, status of traffic lights and associated time period, and a time period required by vehicle to arrive at the traffic lights using machine learning techniques. The method includes providing in real-time the recommended cruising speed to vehicle. The method includes adaptively controlling in real-time speed of vehicle to recommended cruising speed.

Abstract: Physical and logical components of a long line loiter control system address control of a long line loiter maneuver conducted beneath a carrier, such as a fixed-wing aircraft. Control may comprise identifying, predicting, and reacting to estimated states and predicted states of the carrier, a suspended load control system, and a long line. Identifying, predicting, and reacting to estimated states and predicted states may comprise determining characteristics of state conditions over time as well as response time between state conditions. Reacting may comprise controlling a hoist of the carrier, controlling thrusters of the suspended load control system, and or controlling or issuing flight control instructions to the carrier so as not to increase the response time and or to avoid a hazard.

Abstract: This application provides a data processing method and apparatus and a storage medium. The data processing method includes: obtaining K idle calculation blocks in real time, where K is greater than or equal to 1; invoking first K pieces of detected data from a cache stack in a preset priority sequence of detected data, and inputting the detected data into the K idle calculation blocks; sequentially processing K pieces of detected data on the K idle calculation blocks in the preset priority sequence; and integrating sensing calculation results of the K pieces of detected data in real time based on a boundary relationship between detection ranges of the K pieces of detected data, and outputting a sensing result.

Abstract: Technologies and techniques for vehicle perception. A first contour of a current image a dna second contour of a next image are determined relative to an optical center. The current image is scaled to the next image relative to the optical center, wherein the scaling includes applying a scale vector to the first contour. A frame offset vector is determined, and the second contour is translated, based on the frame offset vector and the scale vector, to align the translated second contour to a focus of expansion. An image velocity is determined, based on the first contour and the translated second contour, wherein the image velocity is used to determine object movement from the image data.

Abstract: A transportation system is provided. The system includes: a highway vehicle, a first set of highway points located along a path of the vehicle, a second set of highway points located along a traffic signal section, at least one RFID tag located at each of the first set and the second set of highway points, and at least one RFID tag reader located on the highway vehicle connected to a network. The at least one RFID tag located at the first set of highway points is configured to store dynamic and static characteristics of the highway vehicle as it passes the first set of highway points and the at least one RFID tag located at the second set of highway points is configured to store dynamic and static characteristics of the vehicle as it passes the second set of highway points.