Abstract: A method in a navigational controller includes: obtaining (i) a plurality of task fragments identifying respective sets of sub-regions in a facility, and (ii) an identifier of a task to be performed by a mobile automation apparatus at each of the sets of sub-regions; selecting an active one of the task fragments according to a sequence specifying an order of execution of the task fragments; generating a path including (i) a taxi portion from a current position of the mobile automation apparatus to the sub-regions identified by the active task fragment, and (ii) an execution portion traversing the sub-regions identified by the active task fragment; during travel along the taxi portion, determining, based on a current pose of the mobile automation apparatus, whether to initiate execution of another task fragment; and when the determination is affirmative, updating the sequence to mark the other task fragment as the active task fragment.

Abstract: An unmanned aerial system (UAS) may execute a mission planned by a UAS traffic management (UTM) system. The UAS may receive a mission planning response message from the UTM that includes a mission route for the UAS to navigate and a configuration of one or more trigger events. The mission route may be made up of a sequence of waypoints in an airspace. Each of the waypoints may be configured with a dynamic path conforming profile (PCP) a dynamic required navigation performance (RNP) value. The UAS may monitor at least the RNP value in one or more time intervals to determine if a trigger event occurs. The UAS may transmit a path conformance status report to the UTM upon determining that a trigger event of the one or more trigger events occurred. The path conformance status report may indicate conformance to one or more parameters specified in the PCP.

Abstract: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a navigational system for a host vehicle may include at least one processor programmed to: receive a stream of images captured by a camera onboard the host vehicle, wherein the captured images are representative of an environment surrounding the host vehicle; and receive an output of a LIDAR onboard the host vehicle, wherein the output of the LIDAR is representative of a plurality of laser reflections from at least a portion of the environment surrounding the host vehicle.

Abstract: Systems and methods for operating done flights over public roadways are disclosed herein. An example method includes transmitting, by a first drone, a drone safety message, the drone safety message being received by a vehicle or a roadside infrastructure device located along a first planned flight path, determining an emergency condition for the first done, transmitting a warning message over a vehicle-to-everything communication that indicates that the first drone is experiencing the emergency condition. A connected vehicle or mobile device receives the warning message over the vehicle-to-everything communication. Determining drone operating evidence as the first drone traverses along the first planned flight path, and storing the drone operating evidence in a distributed ledger.

Abstract: A vehicle control device has a processor configured to decide on standby time for waiting until a vehicle that is capable of automatic control for at least one vehicle operation from among driving, braking and steering is to begin the operation for the lane change, based on either first information indicating the degree to which the driver contributes to control of the vehicle or second information representing the extent to which manual control of the vehicle by the driver is possible, the greater the degree to which the driver contributes to control of the vehicle, represented by the first information, or the extent to which manual control of the vehicle by the driver is possible, represented by the second information, the shorter the standby time.

Abstract: The present disclosure is directed to performing one or more validity checks on potential trajectories for a device, such as an autonomous vehicle, to navigate. In some examples, a potential trajectory may be validated based on whether it is consistent with a current trajectory the vehicle is navigating such that the potential and current trajectories are not too different, whether the vehicle can feasibly or kinematically navigate to the potential trajectory from a current state, whether the potential trajectory was punctual or received within a time period of a prior trajectory, and/or whether the potential trajectory passes a staleness check, such that it was created within a certain time period. In some examples, determining whether a potential trajectory is feasibly may include updating a set of feasibility limits based on one or more operational characteristics of statuses of subsystems of the vehicle.

Abstract: The present technology is directed to dynamically adjusting an autonomous vehicle (AV) system based on deep learning optimizations. An AV management system can generate a downscaling signal based on a result of comparing a complexity of an environment for an AV to navigate with a predetermined complexity threshold. Further, the AV management system can perform a downscaling of a neural network associated with an AV system based on the downscaling signal and determine a scenario to test the downscaled neural network in a simulation. The AV management system can adjust one or more parameters of the AV system based on simulated outputs and perform the simulation of the AV based on the adjusted one or more parameters of the AV system and the downscaled neural network to generate simulated performance data. Furthermore, the AV management system can compare the simulated performance data with a predetermined performance threshold.

Abstract: A method for dynamically configuring tasks between a number of manufacturing robots is based on a mechanism for assigning roles for different manufacture requirements. The method includes activating from a library a plurality of roles based on a target manufacturing plan and selecting at least one candidate robot for each activated role based on a plurality of abilities required for each role. The method further assigns activated roles to at least one candidate robot and commands each robot to which one or more roles have been assigned to perform the behaviors corresponding to each activated role, the activated robot then reporting completion of task to their controller.

Abstract: Described herein are various techniques, including systems and non-transitory instructions, that, in response to obtaining information regarding a potential collision between a vehicle and an object, obtain data describing the vehicle for a time period extending before and after a time of the potential collision. The system may determine a likelihood that the potential collision is a non-collision event based on the data describing the vehicle by performing one or more assessments. The assessments may include telematics monitor assessment, driver behavior assessment, road surface feature assessment, trip correlation assessment, and/or context assessment. In response to determining that the likelihood indicates that the potential collision is not a non-collision event, the system may trigger one or more actions responding to the potential collision.

Abstract: Techniques for top-down scene discrimination are discussed. A system receives scene data associated with an environment proximate a vehicle. The scene data is input to a convolutional neural network (CNN) discriminator trained using a generator and a classification of the output of the CNN discriminator. The CNN discriminator generates an indication of whether the scene data is a generated scene or a captured scene. If the scene data is data generated scene, the system generates a caution notification indicating that a current environmental situation is different from any previous situations. Additionally, the caution notification is communicated to at least one of a vehicle system or a remote vehicle monitoring system.

Abstract: The invention relates to a vehicle assistance or control system with a vehicle and with an in particular autonomously drivable offboard obstacle recognition sensor for recognizing obstacles to the vehicle, wherein the vehicle includes an onboard obstacle recognition sensor for recognizing obstacles to the vehicle, wherein the vehicle assistance or control system includes a synchronization circuit for determining the alignment of the offboard obstacle recognition sensor relative to the vehicle, and/or relative to the onboard obstacle recognition sensor depending on an output signal from the offboard obstacle recognition sensor and an output signal from the onboard obstacle recognition sensor.

Abstract: A method for estimating a grip of a tire supporting a vehicle includes generating a first set of data from a tire-mounted sensor unit, generating a second set of data from the tire-mounted sensor unit and from data obtained from the vehicle, and generating a third set of data from data obtained from the vehicle and from the Internet. A grip estimation module is provided. The first, second and third sets of data are received in the grip estimation module. A friction probability distribution is calculated with the grip estimation module using the first, second and third sets of data, and the friction probability distribution is input into at least one vehicle system.

Abstract: An automotive sensor integration module including a plurality of sensors configured to detect an object outside a vehicle, and a signal processing unit configured to output, as sensing data, a plurality of pieces of detection data output from the plurality of sensors according to any one among the plurality of pieces of detection data at a substantially same timing based on a priority signal, or output, as the sensing data, the plurality of pieces detection data according to an external pulse at a substantially same timing.

Abstract: Methods and systems for optimizing the flight of an aircraft are disclosed. The trajectory is divided into segments, each of the segments being governed by distinct sets of equations, depending on engine thrust mode and on vertical guidance (climb, cruise or descent). By assuming two, aerodynamic and engine-speed, models, data from flight recordings are received and a number of parameters from a parameter-optimization engine is iteratively determined by applying a least-squares calculation until a predefined minimality criterion is satisfied. The parameter optimization engine is next used to predict the trajectory point following a given point. Software aspects and system (e.g. FMS and/or EFB) aspects are described.

Abstract: Embodiments describe a method for moisturizing soil at an open construction site. The method includes determining current site characteristics of the open construction site; storing the current site characteristics in memory; determining a target volume of water for achieving a target soil moisture level based on the current site characteristics of the open construction site; calculating a target water application rate to achieve the target soil moisture level across the open construction site; determining a planned path across the open construction site; and guiding a water truck along the planned path while dispensing the target volume of water at the target application rate to achieve the target moisture level in the soil at the open construction site.

Abstract: A control system of a vehicle, the vehicle including a detection unit for detecting external information related to an outside of surroundings of the vehicle, the external information being used to control a driven state of the vehicle is provided. The control system performs a method comprising: obtaining map information of surroundings of a route on which the vehicle travels based on position information of the vehicle, and specifying, from among pieces of detection range information corresponding to the map information, detection range information corresponding to the detection unit; and controlling the driven state of the vehicle based on the specified detection range information and the external information.

Abstract: A vehicle and a system and a method of operating the vehicle. The system includes a reasoning engine, an episodic memory, a resolver and a controller. The reasoning engine infers a plurality of possible scenarios based on a current state of an environment of the vehicle. The episodic memory determines a historical likelihood for each of the plurality of possible scenarios. The resolver selects a scenario from the plurality of possible scenarios using the historical likelihoods. The controller operates the vehicle based on the selected scenario.

Abstract: A vehicle control device of a vehicle includes: an action plan creating part that creates an action plan for autonomous driving by the vehicle; and a distance detection part that outputs detection information on detection of an object. The action plan creating part includes a collision probability map setting part configured to, when the distance detection part detects an obstacle, determine a collision probability map, which is a two-dimensional map of a collision probability distribution representing likelihood of a collision between the vehicle and the detected obstacle in a two-dimensional space of a location and a speed. The action plan creating part is configured to create a current action plan based on the collision probability map, a predetermined target collision probability, and a current location and a current speed of the vehicle.

Abstract: This disclosure is generally directed to systems and methods to sanitize a vehicle. In an example method, a motor vehicle wirelessly transmits a request to sanitize the motor vehicle. The request may be transmitted to an unmanned aerial vehicle (UAV) either directly or indirectly (via a server computer). The motor vehicle then detects the UAV landing upon the roof of the motor vehicle and opens a window of the motor vehicle. The UAV inserts an articulated arm through the open window and into the cabin area of the motor vehicle for executing a sanitizing procedure. The articulated arm can be configured to hold various objects such as a scrubbing pad and/or a container containing a cleaning agent, a sanitizing agent, or a deodorizing agent. In an example scenario, the sanitizing procedure may be directed at eliminating viruses and bacteria that may be present inside the cabin area of the motor vehicle.

Abstract: The system (10) is configured to detect high friction in a steering gear used with a vehicle. The system (10) has a speed sensor (17), a steering angle sensor (17, 108), a plurality of vehicle sensors (23, 112) to monitor vehicle parameters and a plurality of steering system sensors (17, 108) to monitor steering system parameters. A repository stores (27, 120) the normal operating values for the vehicle and steering system sensors (17, 108). A correlation block (21, 130) compares the vehicle and steering system values with the values in the repository (27, 120). A trigger block (15) receives signals from the speed and steering angle sensors, and activating the correlation block (21, 130) when the speed and steering angle sensors are in a select range. The correlation block (21, 130) sends a warning signal if the values from the repository (27, 120) and the signal from the speed and steering angle sensors (17, 108) exceed a predetermined value.