According to one embodiment, a movement control system includes a receiver configured to receive start information for deciding a start order from which execution of an operation plan is started, the operation plan including a plurality of orders for controlling a movable object; and an operation plan executor configured to start the execution of the operation plan from the start order decided based on the start information.

Disclosed are a mover robot system and a controlling method for the same, in which a manipulation of a control screen where a remote control is performed is restricted if a mover robot is located in an area other than a driving area, and a locked screen requesting an input of a preset use code is displayed on a terminal, whereby a display of the locked screen is maintained or released in accordance with the input code.

Techniques disclosed provide for enhanced V2X communications by defining information Elements (IE) for V2X messaging between V2X entities. For a transmitting vehicle that sends a V2X message to a receiving vehicle, these IEs are indicative of a detected vehicle model type detected by the transmitting vehicle of a detected vehicle; a pitch rate of the transmitting vehicle, a detected vehicle, or a detected object; a roll rate of the transmitting vehicle, a detected vehicle, or a detected object; a yaw rate of a detected vehicle, or a detected object; a pitch rate confidence; a roll rate confidence; an indication of whether a rear brake light of a detected vehicle is on; or an indication of whether a turning signal of a detected vehicle is on; or any combination thereof. With this information, the receiving vehicle is able to make more intelligent maneuvers than otherwise available through traditional V2X messaging.

A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.

A vehicle including a magnetic detecting part for detecting a magnetic marker disposed in a road is configured to acquire marker state information indicating the state of the magnetic marker from an external server apparatus via wireless communication and diagnose the state of the magnetic detecting part by using a result of detection of the magnetic marker in which the state of the magnetic marker indicated by the marker state information is good, thereby allowing inspection cost and cost of maintenance of the magnetic detecting part for detecting the magnetic marker to be suppressed.

Systems and methods are provided for machine-learned models including convolutional neural networks that generate predictions using continuous convolution techniques. For example, the systems and methods of the present disclosure can be included in or otherwise leveraged by an autonomous vehicle. In one example, a computing system can perform, with a machine-learned convolutional neural network, one or more convolutions over input data using a continuous filter relative to a support domain associated with the input data, and receive a prediction from the machine-learned convolutional neural network. A machine-learned convolutional neural network in some examples includes at least one continuous convolution layer configured to perform convolutions over input data with a parametric continuous kernel.

A moving robot and a controlling method for the same are disclosed, in which mapping is performed along a wire provided in a boundary of a task area. According to various embodiments disclosed in the present disclosure, since the moving robot self-drives along the wire when setting the task area, a user may acquire map information corresponding to the task area without directly manipulating the moving robot.

A moving robot and a controlling method for the same are disclosed, in which mapping is performed along a wire provided in a boundary of a task area. According to various embodiments disclosed in the present disclosure, since the moving robot self-drives along the wire when setting the task area, a user may acquire map information corresponding to the task area without directly manipulating the moving robot.

The present disclosure provides a method for docking a self-moving device with a charging station, wherein the charging station is connected to a boundary line, and the method comprises the following steps: controlling the self-moving device to move from the current position close to a docking boundary; judging whether the self-moving device senses the boundary line signal during the moving process; if the self-moving device senses the boundary line signal before it reaches the docking boundary or when it reaches the docking boundary, controlling the self-moving device to move towards the charging station through the boundary line signal until the docking is successful; if the self-moving device has not sense the boundary line signal when it reaches the docking boundary, controlling the self-moving device to move from the docking boundary to the boundary line until the boundary line signal is sensed. The present disclosure sets the docking boundary and controls the self-moving device to move close to the docking boundary to find the boundary line, thereby improving the regression efficiency of the self-moving device.

The present disclosure provides a method for docking a self-moving device with a charging station, wherein the charging station is connected to a boundary line, and the method comprises the following steps: controlling the self-moving device to move from the current position close to a docking boundary; judging whether the self-moving device senses the boundary line signal during the moving process; if the self-moving device senses the boundary line signal before it reaches the docking boundary or when it reaches the docking boundary, controlling the self-moving device to move towards the charging station through the boundary line signal until the docking is successful; if the self-moving device has not sense the boundary line signal when it reaches the docking boundary, controlling the self-moving device to move from the docking boundary to the boundary line until the boundary line signal is sensed. The present disclosure sets the docking boundary and controls the self-moving device to move close to the docking boundary to find the boundary line, thereby improving the regression efficiency of the self-moving device.