Disclosed are a platooning control apparatus and control method, the apparatus including a communication unit obtaining performance information and sensing information of a controller for platooning and a control unit granting at least vehicle among plurality of vehicles platooning control authority based on the performance information and in response to determination that a vehicle in which the control unit is provided is the vehicle to be granted platooning control authority, generating a driving route on the sensing information and controlling the platooning based on the driving route.

The present invention relates to a technical idea for providing a delivery service on regular and irregular roads using autonomous vehicles. More specifically, the present invention relates to technology in which, on a regular road, a lead vehicle and at least one droid vehicle are coupled to each other and a delivery service is provided based on autonomous driving; and on an irregular road, the coupling between the lead vehicle and the droid vehicle is automatically released and the droid vehicle provides a delivery service by remotely controlling the driving of the droid vehicle by the lead vehicle in the last mile delivery section corresponding to the irregular road. According to one embodiment of the present invention, a system for providing a delivery service using autonomous vehicles may provide a delivery service on an irregular road where entry of normal vehicles is not allowed and a regular road where entry of small and low-speed vehicles is not allowed and may include a droid vehicle for providing a delivery service using limited autonomous driving performance in a last mile delivery section corresponding to the irregular road; and a lead vehicle for providing a delivery service based on autonomous driving on the regular road, transporting the droid vehicle by being coupled to the droid vehicle on the regular road, and remotely controlling driving of the droid vehicle after being separated from the droid vehicle in the last mile delivery section.

The present disclosure generally relates to autonomous operation of material handling vehicles within a facility, such as a factory or warehouse. An unmanned, autonomous material handling vehicle can encounter a variety of issues operating within the facility, and may need assistance to resolve such issues. The unmanned, autonomous material handling vehicle can transmit a request for assistance to a manned, non-autonomous material handling vehicle, and a human operating the manned, non-autonomous material handling vehicle can assist the unmanned, autonomous material handling vehicle.

This application provides a fleet control method and apparatus, an electronic device, and a storage medium. The fleet control method is used for controlling a robot fleet and includes: determining a planned path of each robot in the robot fleet, where the planned path of each robot is used to indicate a movement path for the robot to move to a corresponding target storage location within a shelving unit region to execute a task; determining a following road segment in the planned path of each following robot based on the planned path of each robot, where the following road segment includes a road segment located on the ground and/or a road segment extending in a vertical direction; and sending the following road segment to a corresponding following robot.

A system for autonomous or semi-autonomous operation of a vehicle is disclosed. The system includes a machine automation portal (MAP) application configured to enable a computing device to (a) display a map of a work site and (b) provide a graphical user interface that enables a user to (i) define a boundary of an autonomous operating zone on the map and (ii) define a boundary of one or more exclusion zones. The system also includes a robotics processing unit configured to (a) receive the boundary of the autonomous operating zone and the boundary of each exclusion zone from the computing device, (b) generate a planned command path that the vehicle will travel to perform a task within the autonomous operating zone while avoiding each exclusion zone, and (c) control operation of the vehicle so that the vehicle travels the planned command path to perform the task.

A robot includes: a communication interface; a sensor configured to obtain distance data; a driver configured to control a movement of the robot; a memory storing with map data corresponding to a space in which the robot travels; and a processor configured to: control the sensor to output a sensing signal for sensing a distance with an external robot, obtain position information of the external robot based on a time at which at least one echo signal is received from the external robot, control at least one of the driver or an operation state of the external robot based on the position information, transmit a control signal for controlling the operation state of the external robot through the communication interface, identify, based on an error occurring in communication with the external robot through the communication interface, a pose of the external robot based on a type of the at least one echo signal received from the external robot, identify a target position of the robot based on the pose of the external robot and the stored map data, and control the driver to move to the target position.

A method performed by a computing system for driving in a group includes determining a plurality of mobility devices included in a first group for group driving. The method also includes identifying a leading device among the plurality of mobility devices included in the first group. The method additionally includes transmitting first route information set in a navigation of the leading device to a trailing device included in the first group together with the leading device. The method further includes setting a first route based on the first route information in a navigation of the trailing device. The method further still includes transmitting second route information set in the navigation of the leading device to the trailing device in response to the leading device deviating from the first route. The method additionally includes setting a second route based on the second route information in the navigation of the trailing device.

A method for assisting a driver in activating an automatic driving mode of a vehicle involves determining the conditions required for an autonomous driving mode and determining a condition not fulfilled in the current driving state which blocks an activation of the autonomous driving mode. An object in the vehicle environment that is in context with an unfulfilled condition is also determined. The object in context with the unfulfilled condition is identified in a representation of the vehicle environment or by projection onto a windscreen, such that a driving maneuver required for enabling an autonomous driving operation is conveyed.

The present disclosure generally relates to autonomous operation of material handling vehicles within a facility, such as a factory or warehouse. An unmanned, autonomous material handling vehicle can encounter a variety of issues operating within the facility, and may need assistance to resolve such issues. The unmanned, autonomous material handling vehicle can transmit a request for assistance to a manned, non-autonomous material handling vehicle, and a human operating the manned, non-autonomous material handling vehicle can assist the unmanned, autonomous material handling vehicle.

A problem of the present invention is to provide an object detection device etc. that can accurately detect an object regardless of a view angle position of and distance to the object. An object detection device of the present invention has: a stereo distance detection portion 105 that detects a distance to an object; a position detection portion 106 that detects a position of the object; a pose detection portion 111 that detects a pose of the object; a vehicle information input portion that inputs state information about a host vehicle and a different vehicle; a position prediction portion 109 that predicts a position of the different vehicle based on the state information about the host vehicle and the different vehicle; a pose prediction portion 110 that predicts a pose of the different vehicle based on the state information about the host vehicle and the different vehicle; and a determination portion 112 that determines a distance to, a position of, and a pose of the different vehicle in response to the information detected or predicted by the distance detection portion, the position detection portion, the pose detection portion, the position prediction portion, and the pose prediction portion.