Robot Wall-Following Control with Continuous Map Prediction Correction
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Solution Overview
Problem
Current autonomous mobile robots face challenges in accurately navigating along walls with varying surfaces due to high costs and false detections associated with distance sensors, and inefficiencies with infrared sensors affected by color and unevenness.
Innovation Solution
A method that combines external sensors with internal map information to estimate and calculate wall surfaces, allowing the robot to walk along predicted surfaces by using collision and obstacle detection sensors to determine straight or arc-shaped routes based on touch points and sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If distance sensors are used to accurately detect wall surface distance, then measurement precision is improved, but device cost increases
Solution Approach 1:
The patent creates a virtual copy of the wall surface by constructing a distance map from robot position and sensor data. Instead of directly measuring wall distance with expensive sensors, the system copies wall position information into a digital map that can be queried computationally, reducing hardware requirements while maintaining measurement accuracy.
Solution Approach 2:
The system performs preliminary mapping of the environment before navigation. By pre-constructing the distance map during exploration phases, the robot has wall position information readily available during motion planning, eliminating the need for real-time expensive distance measurements during actual navigation tasks.
2Device complexity
If infrared sensors are used for wall detection, then device cost is reduced, but measurement precision deteriorates due to wall surface color and unevenness
Solution Approach 1:
The patent introduces an intermediary computational model (distance map) between the simple infrared sensor and the wall detection task. The infrared sensor provides rough distance information, which is then refined through map-based calculations that compensate for sensor limitations and wall surface variations, achieving accurate wall detection without requiring expensive sensors.
Solution Approach 2:
The system uses feedback from the constructed distance map to correct and refine wall position estimates. By continuously updating the map with sensor data and using it to guide subsequent measurements, the system compensates for infrared sensor errors caused by wall surface variations, improving overall detection accuracy.
3Productivity
If the robot follows the predicted wall surface route, then productivity is improved, but reliability may deteriorate when obstacles are not detected
Solution Approach 1:
The patent implements dynamic route adjustment by continuously comparing the predicted wall surface route with real-time sensor data. When obstacles are detected or map predictions diverge from actual conditions, the system dynamically modifies the navigation path, balancing efficient wall-following with adaptive obstacle avoidance to maintain both productivity and reliability.
Data Source
AI summary
A method for controlling a motion of a robot based on map prediction mainly carries out estimation and calculation for a wall surface by combining an external sensor with internal map information about a robot, so as at least to enable the robot to walk along the estimated wall surface. The method for controlling the motion of the robot based on map prediction can be adapted to various different wall surfaces based on map prediction, including different colors and shapes, thereby reducing an operation time; and the accuracy of map prediction can be continuously corrected during an operation process, thereby realizing a good wall-following behavior.