A controller in a vehicle control system includes a communication state determiner that determines a communication state between a facility communicator and a vehicle communicator in each vehicle, and a recorder. When the communication state determiner determines that the communication state between the facility communicator and the vehicle communicator in any vehicle has a communication failure, the controller obtains vehicle state information indicating a state of a target vehicle being the vehicle having the communication failure at at least one data obtaining point in a target period including at least one of a failure-occurrence point or a failure-recovery point of the communication failure, and records the vehicle state information in the recorder.

Current approaches to controlling robots from multiple vendors typically requires multiple software systems that define vendor-exclusive fleet manager or dispatch systems. Autonomous devices (e.g., robots, drones, vehicles) can be controlled from multiple vendors that use multiple locally sourced map. For example, maps from individual robots can be translated to a base map that can be used to command and control hybrid fleets of robots.

Current approaches to controlling robots from multiple vendors typically requires multiple software systems that define vendor-exclusive fleet manager or dispatch systems. Autonomous devices (e.g., robots, drones, vehicles) can be controlled from multiple vendors that use multiple locally sourced map. For example, maps from individual robots can be translated to a base map that can be used to command and control hybrid fleets of robots.

A moving object manufactured in a factory comprises: a driving controller that implements driving control over the moving object by unmanned driving during a course of manufacture of the moving object in the factory; a process completion detector that detects completion of a process by at least one step included in the course of manufacture; and a control content change unit that changes a content in control over the moving object when the completion of the process is detected.

A moving object manufactured in a factory comprises: a driving controller that implements driving control over the moving object by unmanned driving during a course of manufacture of the moving object in the factory; a process completion detector that detects completion of a process by at least one step included in the course of manufacture; and a control content change unit that changes a content in control over the moving object when the completion of the process is detected.

A method of detecting slip between a self-propelled robotic tool and a grass surface comprises: driving on the grass surface; based on a desired heading and speed of the self-propelled robotic tool, generating a first drive signal for a first drive wheel of the self-propelled robotic tool; generating a time-variant drive signal pattern overlay; applying said time-variant drive signal pattern overlay to said first drive signal to form a first wheel control signal; operating a first drive wheel based on said first wheel control signal; receiving a movement signal from a movement detector; and determining a slip state based on an identification of said time-variant drive signal pattern overlay in said movement signal.

A method of detecting slip between a self-propelled robotic tool and a grass surface comprises: driving on the grass surface; based on a desired heading and speed of the self-propelled robotic tool, generating a first drive signal for a first drive wheel of the self-propelled robotic tool; generating a time-variant drive signal pattern overlay; applying said time-variant drive signal pattern overlay to said first drive signal to form a first wheel control signal; operating a first drive wheel based on said first wheel control signal; receiving a movement signal from a movement detector; and determining a slip state based on an identification of said time-variant drive signal pattern overlay in said movement signal.

An intelligent obstacle detection system for an unmanned mine vehicle is provided to solve the problem of existing intelligent obstacle detection systems for unmanned mine vehicles cannot compare and analyze the actual driving data with the preset data and includes an intelligent detection platform, a route planning device, an obstacle detection device, a planning management device, an operation monitoring device, and a storage device. The route planning device is configured to perform route planning analysis for the unmanned mine vehicle to obtain a planned route of the unmanned mine vehicle. The planned route is sent to the obstacle detection device. The intelligent obstacle detection system can plan and analyze the travel route. By locking onto starting and target positions of the unmanned mine vehicles, and then obtaining point cloud data through the detection terminals and calculating with algorithms, the optimal planned route can be determined.

An intelligent obstacle detection system for an unmanned mine vehicle is provided to solve the problem of existing intelligent obstacle detection systems for unmanned mine vehicles cannot compare and analyze the actual driving data with the preset data and includes an intelligent detection platform, a route planning device, an obstacle detection device, a planning management device, an operation monitoring device, and a storage device. The route planning device is configured to perform route planning analysis for the unmanned mine vehicle to obtain a planned route of the unmanned mine vehicle. The planned route is sent to the obstacle detection device. The intelligent obstacle detection system can plan and analyze the travel route. By locking onto starting and target positions of the unmanned mine vehicles, and then obtaining point cloud data through the detection terminals and calculating with algorithms, the optimal planned route can be determined.

Disclosed herein is a method of detecting stalled state of a dynamic pool equipment unit, comprising receiving a plurality of movement features relating to a dynamic pool equipment unit deployed in a water pool which are captured during a predefined sampling window and comprise (1) motion features of the pool equipment unit, and (2) operational features of electric motor(s) of the pool equipment unit, determining a movement pattern of the pool equipment unit using one or more statistical models applied to the plurality of movement features which are trained to estimate a stalled state of the pool equipment unit in which the pool equipment unit is pitched up and unable to advance on a slopped obstacle in the water pool, and causing the pool equipment unit to stop attempted advance in a current direction responsive to determining that the pool equipment unit is in the stalled state.