Self-Moving Robot Obstacle Traversal With Coordinate Turning Points
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Solution Overview
Problem
Existing self-moving robots face inefficiencies in obstacle avoidance, leading to prolonged walking times and complex arithmetic requirements, which impair their working efficiency due to repetitive path navigation around obstacles.
Innovation Solution
A method that establishes a rectangular plane coordinate system with the self-moving robot walking along the X and Y axes, where obstacle points are recorded and used to determine turning points for efficient path adjustment, allowing one-off avoidance actions and concise path navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the self-moving robot walks in a reciprocating manner around obstacles in the vertical direction, then the robot can avoid obstacles, but the walking time is greatly prolonged and working efficiency is impaired
Solution Approach 1:
The robot performs preliminary scanning in the horizontal direction to detect obstacles before completing vertical traversal. When an obstacle is detected, the robot proactively switches to horizontal scanning mode, recording obstacle position coordinates. This preliminary detection and mode switching prevents the robot from repeatedly walking around obstacles in reciprocating vertical paths, thereby resolving the contradiction between reliable obstacle avoidance and maintaining working efficiency.
2Productivity
If the robot uses complex arithmetic to determine obstacle avoidance paths, then the path can be optimized, but the device complexity increases
Solution Approach 1:
The patent replaces complex arithmetic calculations with a coordinate-based detection and recording system. The robot uses sensors to detect obstacles and records their positions as coordinate data. Instead of performing complex path optimization calculations, the system simply compares current position with recorded obstacle coordinates to determine avoidance actions. This substitution of mechanical/computational complexity with a simpler coordinate-based system resolves the contradiction between path optimization and device complexity.
Data Source
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AI summary
An obstacle avoidance walking method of a self-moving robot is provided, comprising: step 1000: the self-moving robot walks along the Y axis, sets the position at which obstacle is detect as an obstacle points and sets the coordinate of the point as a recorded point; step 2000: it is determined whether a recorded point, the Y-axis coordinate of which is within a numerical interval defined by the Y-axis coordinates of the current obstacle point and the previous obstacle point, has been stored previously; step 3000: if the determination result is positive, the recorded point is a turning point, and the self-moving robot walks along the X axis from the current obstacle point toward the turning point to the X-axis coordinate of the turning point, deletes the coordinate of the turning point, and the method returns to the step 1000 after performing traversal walking in an area between the turning point and the current obstacle point; and if the determination result is negative, the self-moving robot shifts for a displacement M1 along the X axis; step 4000: the self-moving robot walks along a reverse direction opposite to the former Y-axis walking direction, and the method returns to the step 1000; step 5000: the step 1000 to the step 4000 are repeated until Y-axis traversal walking is completed. The method accurately determines obstacle position and provides a concise walking path, and greatly improves the working efficiency of the self-moving robot.