Robot Motion Control Using Target Work Area and Obstacle Maps
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Solution Overview
Problem
Current robot control systems lack autonomous danger avoidance capabilities, affecting perception and safety, leading to low operational safety and user experience.
Innovation Solution
A method and apparatus for controlling robots that involve obtaining target actions, environment information, and determining a target work area based on obstacle and ground material information, allowing the robot to autonomously navigate and avoid dangers by generating obstacle maps and determining motion paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If distance sensors are used to detect obstacles and control the robot to perform obstacle avoidance, then the robot can detect obstacles, but the robot cannot avoid dangers autonomously, resulting in low safety of robot operation
Solution Approach 1:
The patent implements a feedback mechanism where the robot continuously obtains environment information through sensors, determines its current work area based on this information, and adjusts its motion path accordingly. The controller receives real-time environmental data, processes it to identify obstacles and unsafe areas, and generates appropriate motion commands to avoid dangers, creating a closed-loop autonomous safety system
Solution Approach 2:
The robot performs autonomous danger avoidance by independently processing environment information itself. The controller determines the current work area and generates motion paths without requiring external intervention. The system uses its own sensors and processing capabilities to identify obstacles and autonomously decide on avoidance maneuvers, enabling self-service safety operation
2Extent of automation
If the robot determines target work area based on environment information and target action, then the robot can autonomously navigate and avoid dangers, but the device complexity increases
Solution Approach 1:
The control system is segmented into distinct functional modules: an obtaining module that collects environment information, a determination module that processes this information to identify the current work area, and a control module that generates motion paths. This modular segmentation allows each component to perform a specific function, making the overall complex system more manageable and implementable through distributed processing
3Measurement precision
If the robot uses sensors to detect obstacle information and generate obstacle maps, then the perception ability of robots is improved, but the use of energy increases
Solution Approach 1:
The robot performs partial sensing by focusing detection efforts on relevant areas rather than continuously scanning the entire environment. The system determines the current work area based on target actions and prioritizes sensing in these specific regions. This partial action approach maintains adequate obstacle detection precision for safe operation while reducing overall sensor energy consumption compared to exhaustive environmental scanning
Data Source
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AI summary
A method for controlling a robot includes: - obtaining a target action of the robot; - obtaining environment information of a working environment where the robot is located; - determining a target work area of the robot based on the environment information and the target action; - controlling the robot to move in the target work area based on the target action.