Robot Work Area Control for Autonomous Danger Avoidance
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Solution Overview
Problem
Current robots lack autonomous danger avoidance capabilities, affecting their 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 and environment information to determine a safe work area, using deep neural networks for ground material analysis and obstacle detection, and navigating the robot to move within this area based on the target action, ensuring safe operation.
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 robot performs self-service by autonomously determining its own working area and navigating within it without human intervention. The controller automatically processes environment information, identifies safe zones, and controls the robot's movement to avoid dangers, enabling the robot to serve itself in safety-critical functions.
Solution Approach 2:
The system implements feedback by continuously obtaining environment information, comparing it with the target working area boundaries, and adjusting the robot's navigation in real-time. The controller monitors the robot's position relative to the determined working area and provides continuous feedback control to maintain safe operation within boundaries.
2Reliability
If the robot operates without autonomous perception capabilities, then the system is simpler, but the perception ability of robots is affected, resulting in low safety of robot operation
Solution Approach 1:
The distance sensor serves multiple functions: it detects obstacles for traditional obstacle avoidance, provides data for determining working area boundaries, and enables autonomous navigation. By making the sensor multi-functional, the system achieves enhanced safety and autonomous perception without proportionally increasing device complexity.
Solution Approach 2:
The patent merges the obstacle detection function and working area determination function into a single integrated process. The controller combines environment information from distance sensors with target action data to simultaneously perform obstacle avoidance and working area boundary determination, reducing overall system complexity while improving safety.
Data Source
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; and controlling the robot to move in the target work area based on the target action.