Abstract: An embodiment pallet stacking apparatus includes a lidar installed in an unmanned forklift and configured to radiate laser light and convert range data reflected from a first cup-feet pallet to 3D point cloud data, a bird's eye view (BEV) conversion unit configured to convert the 3D point cloud data to a 2D BEV image, a cup recognition unit configured to perform channel normalization with input data of the 2D BEV image and recognize a cup position through calculation using convolutional neural network, a forklift controller configured to control operation of the unmanned forklift according to a control signal, and a control unit configured to identify a difference between a cup position of the first cup-feet pallet and a cup position of a stationary second cup-feet pallet and apply a control signal for adjustment to a matching position to the forklift controller.

Abstract: Systems and techniques are described for implementing autonomous control of powered earth-moving vehicles, including to automatically determine and control movement around a site having potential obstacles. For example, the systems/techniques may determine and implement autonomous operations of powered earth-moving vehicle(s) (e.g., obtain/integrate data from sensors of multiple types on a powered earth-moving vehicle, and use it to determine and control movement of the powered earth-moving vehicle around a site), including in some situations to implement coordinated actions of multiple powered earth-moving vehicles and/or of a powered earth-moving vehicle with one or more other types of construction vehicles.

Abstract: Activating an engine of a HEV to charge a battery includes obtaining a first GPS trace from a first trip of the HEV along a first route, where the first GPS trace includes first trace metadata; obtaining a second GPS trace from a second trip, where the second GPS trace includes second trace metadata; adding, to a navigation map, an aggregation of the first trace metadata and the second trace metadata for edges of the navigation map; using the navigation map to obtain an activation action of the engine, where the activation action is selected from a set that includes a first activation action of turning the engine on and a second activation action of turning the engine off; and activating the engine according to the activation action, where activating the engine using the first activation action causes the engine to turn on to charge the battery of the HEV.

Abstract: A system and method includes a wireless receiver and/or receiver-transceiver integrated into one of a powertrain electrical system, ECU, MCU, and vehicle speed output sensors of the high-performance vehicle, a speed command control device integrated into the wireless receiver and/or receiver-transceiver to automatically turn ON at a predetermined vehicle speed, and a transmitter and/or transmitter-transceiver operable by law enforcement to transmit RF messaging packets to the wireless receiver and/or receiver-transceiver when the speed command control device is activated by the transmitter and/or transmitter-transceiver to reduce the speed of the high-performance vehicle. The method may implement Vehicle Speed Ship Mode (VSSM) with the same, similar, or different RF receiver and/or receiver-transceiver by turning ON the speed bit indefinitely by use of custom factory software and or factory tool.

Abstract: A method for operating a higher-level automated vehicle (HAV), in particular a highly automated vehicle, is provided, including: S1 for providing a digital map, which may be a highly accurate digital map, in a driver assistance system of the HAV; S2 for determining an instantaneous vehicle position and localizing the vehicle position in the digital map; S3 for providing an expected setpoint traffic density at the vehicle position; S4 for ascertaining an instantaneous actual traffic density in the surroundings of the HAV; S5 for comparing the actual traffic density to the setpoint traffic density and ascertaining a difference value as the result of the comparison; S6 for checking the vehicle position of the HAV for plausibility at least partially based on the difference value and/or S7 for updating the digital map at least partially based on the difference value. Also described are a corresponding driver assistance system and a computer program.

Abstract: A safety system for localizing a movable machine having a safety controller, having at least one radio location system, and having at least one sensor for position determination, wherein the radio location system has radio stations arranged as stationary, wherein at least one radio transponder is arranged at the movable machine, wherein position data of the movable machine can be determined by means of the radio location system, wherein the position data can be transmitted from the radio station or from the radio transponder of the radio location system to the safety controller and position data of the movable machine can be determined by means of the sensor, and wherein the safety controller is configured to compare the position data of the radio location system and the position data of the sensor and to form checked position data on agreement.

Abstract: An example operation includes one or more of determining a transport, in a group of transports associated with a date of disposition, is operating below an efficiency threshold of the group of transports, and limiting transports, in the group of transports, that are operating most above the efficiency threshold, from performing functionality until the group of transports is at the efficiency threshold.

Abstract: An automated guided vehicle (AGV) management system including a battery recharge management module, a task management module, and an AGV path planning module is provided. The battery recharge management module manages the AGVs to be recharged by at least one wireless charging unit in a parking area. The AGV leaving the parking area has a battery charge higher than a charge threshold. The task management module receives tasks and assigns the tasks to the AGVs. The task includes information including at least one pick-up location, at least one drop-off location, and a due time. The AGV path planning module plans paths for the AGVs, respectively, according to the information of the assigned tasks. The task management module delays assigning the task to the AGV if the AGV is expected to complete the task earlier than the due time of the task.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining respective importance scores for a plurality of agents in a vicinity of an autonomous vehicle navigating through an environment. The respective importance scores characterize a relative impact of each agent on planned trajectories generated by a planning subsystem of the autonomous vehicle. In one aspect, a method comprises providing different states of an environment as input to the planning subsystem and obtaining as output from the planning subsystem corresponding planned trajectories. Importance scores for the one or more agents that are in one state but not in the other are determined based on a measure of difference between the planned trajectories.

Abstract: A hybrid vehicle, a control method therefor, and a storage medium which are capable of suppressing changes in an engine sound and vibration even when acceleration is performed at the time of increasing a required driving force are provided. In a hybrid vehicle capable of performing automated driving control for automatically controlling at least acceleration and deceleration of a vehicle, a rotational speed of the engine is gradually increased by a predetermined increase step while maintaining or decelerating a vehicle speed of the hybrid vehicle until an increase timing of a required driving force in a case where it is predicted that the required driving force is required to be increased while the automated driving control is performed, and at least the power generated by the generator is supplied to the motor at the increase timing of the required driving force.

Abstract: A method for determining routes for test drives of autonomous vehicles, wherein a plurality of test features are to be encountered or avoided on the routes. The method includes determining a geographical area in which a test drive is to take place, determining a starting point, determining a destination point, determining the plurality of test features, which are relevant for the test drive, creating a logical expression which places the plurality of test features in a logical relationship to one another, determining, at least one route which are located within the geographical area, which have the starting point and the destination point and which satisfy the logical expression, using a map material for the area and positions or areas where the plurality of test features are located, and displaying a representation of the determined routes for a user for the purpose of selecting a selected route.

Abstract: A method for controlling at least one industrial truck comprising determining a driving job using a superordinate control unit and sending the driving job from the superordinate control unit to a transceiver of the at least one industrial truck. The driving job is transmitted from the transceiver to a vehicle controller. A position of the at least one industrial truck within a previously known route to be driven is determined via the superordinate control unit. An upcoming driving situation is identified using the superordinate control unit and is based on the position of the at least one industrial truck and the driving job. A protective field is generated with a collision protection apparatus, wherein the protective field is monitored by the at least one industrial truck based on the upcoming driving situation even before the at least one industrial truck reaches the driving situation.

Abstract: A navigation request is detected. The navigation request includes a destination for an autonomous vehicle from a starting location. A route is identified from the starting location to destination based on the navigation request. A regulator lookup is performed related to the route based on the navigation request. The regulator lookup is related to an owner of privacy data for one or more regulators. In response to the regulator lookup, a conditional allowance related to the route is received. The conditional allowance indicates that one or more autonomous vehicle sensors of the autonomous vehicle may not capture data related to a first property of a first regulator. the first property is located proximate to the route. The one or more autonomous vehicles sensors of the autonomous vehicle are restricted in response to the conditional allowance.

Abstract: The embodiments provide a method for unmanned vehicle cruising, an unmanned vehicle and a storage medium, the method includes: in a state that a slow cruising function is started, cruising according to a preset cruising mode, and collecting running data through a sensing device, where the running data is data of an environment in which a vehicle locates, collected by the vehicle during a running process; and generating a map based on the collected running data. The embodiments of the present disclosure solve the problem that an unmanned vehicle in the prior art cannot update a map in time and, in particular, cannot develop a more suitable map according to different surrounding environments.

Abstract: A method of controlling a vehicle or robot. The method includes the following steps: determining a first control sequence, determining a second control sequence for controlling the vehicle or robot depending on the first control sequence, a current state of the vehicle or robot, and on a model characterizing a dynamic behavior of the vehicle or robot, controlling the vehicle or robot depending on the second control sequence, wherein the determining of the first control sequence is performed depending on a first candidate control sequence and a second candidate control sequence.

Abstract: Provided is an automated guided vehicle that travels on a traveling path by loading at least one of a member required for a production work in which production equipment produces a product and a production tool detachable to the production equipment, and shares at least a portion of the traveling path with another automated guided vehicle, in which a traveling priority is variably set based on a work priority determined from a status of the production work, and when the traveling priority of the automated guided vehicle is higher than the traveling priority of the another automated guided vehicle, the automated guided vehicle is prioritized for traveling on the traveling path.

Abstract: An information processing apparatus of this application includes a controller. The controller is configured to execute: identifying a behavior pattern of a user using a behavior model of the user, the behavior model being generated based on past behavior information of the user detected by a sensor capable of detecting the behavior information of the user, predicting a scheduled arrival time, which is an arrival time of the user at a building to which the user travels, based on the identified behavior pattern of the user, and providing information to the user regarding the movement to the building so that the user can arrive at the building by the predicted scheduled arrival time.

Abstract: A method for specifying a cleaning area to a cleaning robot without an in-built map provides a hand-held mobile device capturing a two-dimensional code label arranged on a top of a cleaning robot parked on a charging base, and obtaining a positional relationship between the mobile device and the cleaning robot through the captured image. The cleaning robot is controlled to enter a cleaning mode under the guidance of the mobile device. With captured images, a user can specify an area within the environment for cleaning, and through a touch display screen can control the cleaning robot to go to the specified cleaning area for cleaning. The mobile device and the cleaning robot employing the method are also disclosed.

Abstract: In one example, a method may include capturing two-dimensional (2D) images of scenes using a set of multi-resolution cameras disposed on at least one side of an autonomous vehicle. Further, a low-resolution depth map with relatively small depths may be generated for each scene using the captured 2D images. Furthermore, a high-resolution depth map may be generated for each scene for a wide depth range by iteratively refining the low-resolution depth map for each scene. Also, a 3D video may be generated based on the high-resolution depth maps and the captured 2D images of the central camera. Further, a distance, a velocity, and/or an acceleration of one or more objects relative to the autonomous vehicle is computed by analyzing one or more frames of the 3D video. Then, the autonomous vehicle may be controlled based on the computed distance, velocity, and/or acceleration of the one or more objects.

Abstract: The present disclosure discloses a navigation map updating method as well as an apparatus, and a robot using the same. The method includes: controlling a robot to move along a designated path after a successful relocalization of the robot, and recording key frame data of each frame on the designated path and a corresponding pose; creating a new navigation map, and copying information in an original navigation map into the new navigation map; and covering the key frame data of each frame on the designated path onto the new navigation map to obtain an updated navigation map. In this manner, there is no need for the user to manipulate the robot to recreate the map at the environment where the robot is operated, which saves a lot of time and manpower.