Robot Arc Path Control for Obstacle-Free Bow Transitions
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Solution Overview
Problem
Sweeping and lawn mowing robots face challenges in navigating bow-shaped transitions due to their shape, leading to potential collisions with obstacles, which can cause damage and reduce efficiency.
Innovation Solution
A robot control method that involves obtaining obstacle and target point information, simulating rotation to assess collision risk, planning an arc path, and controlling the robot to move along this path to avoid obstacles, using modules for obstacle detection, collision prediction, and path planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the robot uses traditional rotation-based escape method during bow-shape transition, then the control logic is simple, but the robot may collide with obstacles due to its shape
Solution Approach 1:
The system performs preliminary collision detection by simulating the robot's rotation trajectory before actual movement. The detection unit calculates the robot's occupation area during rotation and checks for intersections with obstacles in advance, preventing collisions before they occur.
Solution Approach 2:
An intermediate occupation area model is introduced between the robot and obstacles. This virtual area representation allows the system to detect potential collisions by checking whether the occupation area intersects with obstacle positions, providing a buffer zone for safe navigation.
2Measurement precision
If the robot uses arc path planning to avoid obstacles, then collision avoidance accuracy is improved, but the control complexity increases
Solution Approach 1:
The system employs curved arc paths instead of straight-line trajectories for robot navigation. When obstacles are detected, the planning unit generates arc-shaped escape paths that naturally bypass obstacles, improving avoidance accuracy while maintaining smooth robot motion.
Solution Approach 2:
The system dynamically adjusts path planning parameters based on robot state and obstacle position. By changing parameters such as arc radius, rotation angle, and transition points according to real-time conditions, the system achieves accurate obstacle avoidance without requiring overly complex algorithms.
3Productivity
If the robot rotates to escape from trap during bow-shape transition, then the escape capability is improved, but the risk of colliding with obstacles increases
Solution Approach 1:
The system implements real-time feedback by continuously monitoring the robot's occupation area during rotation and comparing it with obstacle positions. The detection unit provides immediate feedback on potential collisions, allowing the control unit to adjust or cancel rotation commands to prevent harmful collisions.
Solution Approach 2:
The system applies preliminary anti-action by detecting potential collision trajectories before the robot actually moves into dangerous positions. The occupation area calculation and obstacle intersection check occur in advance, enabling the system to counteract potential harmful effects before they manifest.
Data Source
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AI summary
The present embodiment discloses a robot control method, electronic device and storage medium. The method comprises: obtaining information of an obstacle, location information of a target point, and control basic information of the robot; Simulating rotation based on the information of the obstacle information and the rotation dimension of the robot, judging whether the robot will collide with the obstacle during the rotation process; If it will collide with the obstacle, planning the arc path based on the location information of the target point and the control basic information, and obtaining the target path and a transition point on the target path; Controlling the robot to move towards the transition point according to the target path, and move towards the target point direction from the transition point. Based on this, this application combines simulation rotation with arc path planning to maximize the avoidance of robot collisions with obstacles, making obstacle avoidance more accurate, avoiding collision damage, and improving the work efficiency of the robot.