Abstract: A drone flight plan between an origin and destination is evaluated with respect to planned routes of connected vehicles. The drone flight path is calculated such that it includes one or more docking segments on one or more vehicles. For multiple vehicles, multiple permutations of docking segments may be evaluated and assigned scores according to risk, drone flying time, timing issues, and other factors. A permutation having a score indicating higher desirability may be selected. The one or more vehicles may be autonomous and routes of the one or more vehicles may be adjusted in order to provide suitable docking segments for the drone flight path. The destination of the drone flight path may also be adjusted in order to permit docking on one or more vehicles.

Abstract: An integrated control apparatus for an autonomous vehicle includes a mobile control device 10, which is a portable device manipulated by a user, configured to perform steering, speed change, acceleration and braking of the vehicle, and a touch-type stationary display device 20 manipulated in a touch manner by the user and configured to perform functions other than the steering, the speed change, the acceleration and the braking of the vehicle when the vehicle is shifted from an autonomous driving mode to a manual driving mode. A steering dial switch and a speed change slide switch of the mobile control device are manipulated in a manner different from that in which an acceleration button switch and a braking button switch of the mobile control device are manipulated.

Abstract: Broadcasting geolocation information of an Unmanned Aerial Vehicle (UAV) from the UAV by determining current geolocation of the UAV by communicating with a geolocation service and utilizing the geolocation service to geolocate the UAV. Then the UAV prepares a radio frame that includes geolocation information identifying the current geolocation of the UAV and other information associated with the UAV using a radio protocol of one of a 3rd Generation Partnership Project (3GPP) radio protocol, a WiFi radio protocol, a wireless personal area network protocol and a low-power wide-area network protocol and transmits the radio frame to broadcast the current geolocation of the UAV.

Abstract: A system for determining areas of discrepancy in flight for an electric aircraft is presented. The system includes a plurality of sensors, wherein each sensor is communicatively connected to a flight component and configured to detect a measured flight and generate a flight phase datum. The system further includes a computing device communicatively connected to the plurality of sensors, wherein the computing device is configured to determine, by a flight phase machine-learning model, a flight phase discrepancy datum. The computing device is configured to train the flight phase machine-learning using a flight phase training set, wherein the flight phase training set correlates a flight phase to a flight standard and output the flight phase discrepancy datum. The computing device is further configured to identify an anomalous performance phase as a function of the flight phase discrepancy datum and generate a discrepancy response.

Abstract: Exemplary embodiments described in this disclosure are generally directed to a collaborative relationship between a vehicle and a UAV. In one exemplary implementation, a computer that is provided in the vehicle uses images captured by an imaging system in the UAV together with images captured by an imaging system in the vehicle, to modify a suspension system of the vehicle based on a nature of the terrain located below, or ahead, of the vehicle. The computer may, for example, modify a suspension system before the vehicle reaches a rock or a pothole on the ground ahead. In another exemplary implementation, the computer may generate an augmented reality image that includes a 3D model of the vehicle rendered on an image of a terrain located below, or ahead of, the vehicle. The augmented reality image may be used by a driver of the vehicle to drive the vehicle over such terrain.

Abstract: A method for setting a target flight path of an aircraft in a physical environment, the method includes: displaying a virtual three-dimensional model corresponding to the physical environment; setting a start point in the virtual three-dimensional model according to a user input indicative of a position of the start point; continuously tracking a trajectory of a physical object moved in a space corresponding to the virtual three-dimensional model while displaying within the virtual three-dimensional model a continuous path corresponding to the trajectory of the physical object from the start point; setting an end point of the continuous path in the virtual three-dimensional model according to a user input indicative of a position of the end point; and generating the target flight path of the aircraft in the physical environment based on the continuous path from the start point to the end point in the virtual three-dimensional model.

Abstract: Systems and methods are provided for adjusting a control of a vehicle system based on a condition of an occupant. The system includes a replaceable or upgradeable electronic skin removably coupled to an interior vehicle component. The electronic skin includes at least one sensor positioned therein, configured to monitor/obtain a biometric, physiological, or wellness condition measurement from an occupant. The system includes one or more processors and a memory communicably coupled thereto. An occupant comfort module is provided including instructions that, when executed, collect and monitor feedback from the at least one sensor; determine that the feedback exceeds a predetermined threshold; and determine an adjustment for a vehicle system based on the feedback. A control module may be provided including instructions that, when executed by the one or more processors, cause the vehicle system to change at least one setting based on the adjustment determined by the occupant comfort module.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for robot motion planning using unmanned aerial vehicles (UAVs). One of the methods includes determining that a current plan for performing a particular task with a robot requires modification; in response, generating one or more flight plans for an unmanned aerial vehicle (UAV) based on a robotic operating environment comprising the robot; obtaining, using the UAV in accordance with the one or more flight plans, a new measurement of the robotic operating environment comprising the robot; and generating, based at least on a difference between the new measurement of the robotic operating environment and a previous measurement of the robotic operating environment, a modified plan for performing the particular task with the robot.

Abstract: A method of controlling a hybrid-electric aircraft powerplant includes running a first control loop for command of a thermal engine based on error between total response commanded for a hybrid-electric powerplant and total response from the hybrid-electric powerplant. A second control loop runs in parallel with the first control loop for commanding the thermal engine based on error between maximum thermal engine output and total response commanded. A third control loop runs in parallel with the first and second control loops for commanding engine/propeller speed, wherein the third control loop outputs a speed control enable or disable status. A fourth control loop runs in parallel with the first, second, and third control loops for commanding the electric motor with non-zero demand when the second control loop is above control to add response from the electric motor to response from the thermal engine to achieve the response commanded.

Abstract: The steering control apparatus determines whether or not a deviation degree of a current traveling route of a vehicle with respect to a target traveling route is equal to or more than a predetermined threshold, when steering control is switched from manual steering control to automatic steering control. In the automatic steering control, a command steering angle is calculated so that a difference between a real traveling route of the vehicle and the target traveling route is eliminated. However, when the deviation degree is equal to or more than the predetermined threshold, the steering control apparatus recalculates the command steering angle used in the command steering angle tracking control based on a steering angle at the time of starting the automatic steering control and the command steering angle so that a real steering angle after switching to the automatic steering control changes gradually to the command steering angle.

Abstract: A system for detecting the levelness of ground engaging tools of a tillage implement including an agricultural implement including a frame and ground engaging tools supported relative to the frame. The system includes a first sensor and a second sensor configured to capture data indicative of a material flow past one or more first ground engaging tools and second ground engaging tools, respectively. The system includes a controller configured to monitor data received from the first sensor and the second sensor and compare one or more first monitored values and one or more second monitored values associated with the material flow past the first ground engaging tool(s) and the second ground engaging tool(s), respectively. The controller is further configured to identify that at least a portion of the ground engaging tools are not level when the first monitored value(s) differs from the second monitored value(s) by a predetermined threshold value.

Abstract: A computer implemented method for controlling a system moving through an environment includes receiving a stream of event data from an event camera, the stream of event data representing a pixel location, a time stamp, and a polarity for each event detected by the event camera. A compressed representation of the stream of data is generated. The compressed representation is provided to a neural network model trained on prior compressed representations using reinforcement learning to learn actions for controlling the system. A control action is generated via the neural network model to control the movement of the system.

Abstract: An approach is provided for an unknown moving object detection system. The approach, for instance, involves capturing a plurality of unknown object events indicating an unknown object detected by one or more computer vision systems. The approach also involves clustering the plurality of unknown object events into a plurality of clusters based on one or more clustering parameters. The approach further involves selecting at least one cluster of the plurality of clusters based on a selection criterion. The approach further involves determining at least one operating scenario for the one or more computer vision systems based on a combination of the one or more clustering parameters associated with the selected at least one cluster.

Abstract: Breakaway detection and alerting is described for a towed vehicle. In one example, a system includes a wired breakaway detector having a detector to generate an electric breakaway detection signal when a breakaway cable is not in a breakaway cable socket and an electrical cable to indicate the electric breakaway detection signal, and a wireless interface configured to be attached to the towed vehicle outside of the interior driver's area, to receive the electric breakaway detection signal from the breakaway detector and having a wireless transceiver to transmit a wireless breakaway alert signal in response to receiving the electric breakaway detection signal. A portable brake activation system receives the wireless breakaway alert signal from the wireless interface in the interior driver's area of the towed vehicle and activates the towed vehicle braking system through the attached brake pedal in response to the wireless breakaway alert signal.

Abstract: Provided is a storage device storing a movement assistance program, the program being configured to cause a computer to implement the functions of: a terrain information acquisition instruction section that instructs a terrain information acquisition device mounted on a flying machine to acquire terrain information representing a terrain lying between a present location of a ground-moving machine and a destination; a zone classification section that makes a classification based on a predetermined movement permission condition and the terrain information to divide the terrain lying between the present location and the destination into a movement-permitted zone and a movement-prohibited zone; and an output section that outputs at least one selected from a movement route of the ground-moving machine, the movement-permitted zone, and the movement-prohibited zone, the movement route leading from the present location to the destination without passing through the movement-prohibited zone.

Abstract: The autonomous LC control is started in response to receiving a start instruction of autonomous lane change. When the driver performs a steering intervention in a same direction as a direction of steering requested by the autonomous LC control, and establishment of a stop condition of lane change is not recognized, during execution of the autonomous LC control, the autonomous driving control is continued. When the steering intervention in the same direction is performed, and establishment of the stop condition is recognized, during execution of the autonomous LC control, termination of the autonomous driving control is announced.

Abstract: A vehicle display device, that includes: a first display device provided inside a vehicle cabin; a second display device provided inside the vehicle cabin and separately from the first display device; a memory; and a processor connecting to the memory and being configured to: set a running plan of a vehicle, to display a scheduled action of the vehicle on the first display device based on the running plan, and to display the scheduled action on the second display device in a case in which at least one of a distance to, or a time interval until, the scheduled action has reached a prescribed value or less.

Abstract: A system configured to cause a vehicle to autonomously maneuver to a safe haven during a triggering event includes a communication component configured to receive parameters corresponding with conditions of the triggering event and, based on the parameters and on characteristics of the safe haven, instruct the vehicle to maneuver to the safe haven.

Abstract: Systems, methods, and computer-readable media, are disclosed in which a variety of data describing the condition of an object can be obtained and probabilistic likelihoods of causes and/or value of damages to the object can be calculated. In a variety of embodiments, data obtained from third-party systems can be utilized in these calculations. Any of a number of machine classifiers can be utilized to generate the probabilistic likelihoods and confidence metrics in the calculated liabilities. A variety of user interfaces for efficiently obtaining and visualizing the object, the surrounding geographic conditions, and/or the probabilistic likelihoods can further be utilized as appropriate to the requirements of specific applications of embodiments of the invention.

Abstract: A device is provided to extract scan lines data from images of a route, said scan line data comprising only a portion of the an image that extends along a scan line, and to store this data in memory together with respective positional data pertaining to the position of the device traveling along the route in a navigable network. This scan line and positional data can be obtained from a plurality of devices in a network and transmitted to computing apparatus, for example, for use in a production of a realistic view of a digital map.