Self-Moving Robot Obstacle Avoidance with Turning-Point Path Planning
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Solution Overview
Problem
Existing self-moving robots inefficiently navigate around obstacles, leading to prolonged walking times and reduced working efficiency due to repetitive path changes.
Innovation Solution
A method that uses a rectangular plane coordinate system to classify and store obstacle points, determining turning points based on Y-axis coordinates to allow one-off obstacle avoidance, thereby optimizing walking paths and reducing repetitive navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the self-moving robot uses traditional obstacle avoidance walking method, then the robot can avoid obstacles, but the walking time is prolonged and working efficiency is impaired
Solution Approach 1:
The robot performs preliminary mapping of the environment to identify obstacles before actual navigation. By pre-processing the spatial information and planning the walking path in advance, the robot avoids time-consuming real-time obstacle detection and repetitive path adjustments during movement, thus reducing walking time while maintaining reliable obstacle avoidance
Solution Approach 2:
The robot dynamically adjusts its walking path based on real-time obstacle detection and the pre-established map. Instead of following fixed reciprocating paths, the system continuously optimizes the navigation route by integrating sensor data with the environmental model, enabling adaptive path planning that minimizes walking time while ensuring safe obstacle avoidance
2Productivity
If the self-moving robot follows reciprocating paths, then the robot can systematically cover the walking area, but repetitive path changes occur when encountering obstacles
Solution Approach 1:
The walking area is segmented into multiple zones or regions, and the robot systematically covers each zone using optimized path planning. By dividing the environment into manageable segments and applying intelligent navigation algorithms to each segment, the system achieves comprehensive area coverage while avoiding the complexity of managing repetitive global path changes
Solution Approach 2:
The robot employs feedback mechanisms where sensor data about obstacles and environmental features is continuously fed back to the path planning system. This feedback loop enables the robot to adjust its trajectory in real-time based on actual conditions, maintaining systematic area coverage while dynamically simplifying the path planning by avoiding pre-planned repetitive routes that would require frequent changes
Data Source
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.