An apparatus and the like for controlling a mobile body that are capable of adjusting a detection result by a radar device in accordance with a three-dimensional shape for each region of a three-dimensional map generated from an image captured by an image-capturing device are provided. A mobile body control unit 105 is an apparatus for controlling the vehicle (mobile body) including an image-capturing device 101 and a millimeter wave radar device 102 (radar device). A three-dimensional map generation unit 203 generates a three-dimensional map around the vehicle from an image captured by the image-capturing device 101. A radar weight map estimation unit 204 (weight estimation unit) estimates the weight of the detection result by the millimeter wave radar device 102 for each region of the three-dimensional map from the three-dimensional shape for each region of the three-dimensional map. A weight adjustment unit 205 (adjustment unit) adjusts a detection result by the millimeter wave radar device 102 on the basis of a weight.

Embodiments of the disclosure provide a transfusion guiding robot and a guiding method for guiding a movement of a transfused person. The transfusion guiding robot comprises a controller, a moving portion and a fixing portion. The controller is configured to receive and process instruction information, and control the transfusion guiding robot according to the instruction information; the moving portion is configured to move according to a command from the controller; and the fixing portion is configured to fix a container, a height of the fixing portion being adjustable.

An ambient sound environment is captured by a microphone array of an autonomous vehicle traveling in the ambient sound environment. A perception module of the autonomous vehicle classifies sounds and localizes sound sources in the ambient sound environment. Classification is performed using spectrum analysis and/or machine learning. In an embodiment, sound sources within a field of view (FOV) of an image sensor of the autonomous vehicle are localized in a visual scene generated by the perception module. In an embodiment, one or more sound sources outside the FOV of the image sensors are localized in a static digital map. Localization is performed using parametric or non-parametric techniques and/or machine learning. The output of the perception module is input into a planning module of the autonomous vehicle to plan a route or trajectory for the autonomous vehicle in the ambient sound environment.

Among other things, planning a motion of a machine having moving capabilities is based on strategic guidelines derived from various basic principles, such as laws, ethics, preferences, driving experiences, and road environments.

The angle of a trailer with respect to a tow vehicle is an important parameter to the stability of the vehicle and trailer. A tow vehicle pulling a trailer in a straight line is generally more stable than when the vehicle is turning. While turning, the angle between the tow vehicle and the trailer is not a straight line but is another angle depending on how sharply the tow vehicle is turning. To safely operate a vehicle towing a trailer, for a given steering input and speed, there is a maximum angle between the tow vehicle and trailer whereby exceeding the angle causes instability and may cause the trailer or tow vehicle to roll over or jackknife. Accordingly, the angle between the trailer and tow vehicle must be determined to ensure the vehicle and trailer will continue to be in control.

The disclosed subject matter includes a method and system for navigating an unmanned ground vehicle (UGV), that include: generating, based on the scanning output data, a first map comprising a first group of cells and characterized by a first size; generating, based on the scanning output data, a second map representing an area smaller than that of the first map comprising a second group of cells, which are characterized by a second size being smaller than the first size; wherein each cell in the first group of cells and the second group of cells is classified to a class selected from at least two classes, comprising traversable and non-traversable, wherein the second part at least partly overlaps the first part; navigating the UGV based on data deduced from crossing between cells in the first map and second map.

The present invention relates to a driverless transport system (81), comprising a plurality of driverless transport devices (10) having a support structure (12) with an outer contour (14); an undercarriage (16) which is secured to the support structure (12) and has at least one first wheel (18) and a second wheel (20), wherein the first wheel (18) is mounted in the undercarriage (16) so as to rotate about a first axis of rotation (D1) and the second wheel (20) is mounted in the undercarriage (16) so as to rotate about a second axis of rotation (D1); a drive unit (22) by means of which the first wheel (18) and the second wheel (20) can be driven independently of each other; a control unit (94) for controlling or regulating the driverless transport devices (10); and a communication device (76) by means of which information can be exchanged between the control unit (94) and the driverless transport devices (10), wherein one of the driverless transport devices (10) is designed as a master (86) and the other driverless transport devices (10) are designed as slaves (88).

A vehicle control system for an agricultural vehicle including a processing circuit including a processor and memory, the memory having instructions stored thereon that, when executed by the processor, cause the processing circuit to receive (i) image data depicting at least a portion of a hazard area associated with the agricultural vehicle and (ii) ultrasonic sensor data from an ultrasonic sensor monitoring the hazard area, determine, based on a combination of the image data and the ultrasonic sensor data, whether an obstacle is positioned at least partially within the hazard area, and perform an action with respect to the agricultural vehicle in response to a determination that the obstacle is positioned at least partially within the hazard area.

Provided is a process that includes: obtaining a first version of a map of a workspace; selecting a first undiscovered area of the workspace; in response to selecting the first undiscovered area, causing the robot to move to a position and orientation to sense data in at least part of the first undiscovered area; and obtaining an updated version of the map mapping a larger area of the workspace than the first version.

A method of controlling a guide machine and a navigation system. The navigation system includes: a plurality of signal sources deployed in a predetermined area; a guide machine including a signal receiver arranged to receive electromagnetic signals emitted from one or more of the plurality of signal sources; and a processor arranged to process the electromagnetic signals to identify the locations of the signal sources, and thereby to determine a current position of the guide machine with reference to the locations of the signal sources; and the processor is further arranged to determine a path for the guide machine to travel from the current position to a destination location in the predetermined area.