Robot Wall-Following Control Using Predictive Wall Maps
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Solution Overview
Problem
Existing autonomous mobile robots face challenges in accurately navigating along walls with uneven surfaces due to high costs and false detections associated with distance sensors, and inefficiencies with infrared sensors affected by color and texture.
Innovation Solution
Combining external sensors with internal map information to estimate and calculate the wall surface, allowing the robot to walk along predicted paths, using collision detection and obstacle sensors to adapt to various wall surfaces, including those with pillars and irregular shapes.
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 map copy of the wall surface based on initial distance measurements and robot motion data. This virtual map is then used for continuous position estimation without requiring ongoing use of expensive distance sensors, thus achieving accurate wall following at lower operational cost
Solution Approach 2:
The system performs preliminary wall surface mapping and feature extraction before actual navigation. By pre-processing the environment data and creating a predictive model of wall positions, the robot can navigate using this pre-computed information rather than continuous expensive sensing
2Device complexity
If infrared sensors are used for wall detection, then device cost is reduced, but measurement precision deteriorates due to color and unevenness effects
Solution Approach 1:
The patent introduces a virtual map as an intermediary between the infrared sensor and the wall following control. The infrared sensor provides rough distance estimates, which are then refined using the virtual map model to compensate for detection errors caused by surface color and texture variations
Solution Approach 2:
The system continuously compares actual infrared sensor readings with predicted wall positions from the virtual map, using the difference to correct navigation errors. This feedback mechanism compensates for infrared sensor inaccuracies without requiring more expensive sensors
3Reliability
If robots follow walls using traditional sensor methods, then navigation capability is maintained, but operation time increases due to false detections and corrections
Solution Approach 1:
The virtual map is constructed in advance during an initial mapping phase, storing wall surface features and positions. During subsequent navigation tasks, the robot directly references this pre-computed map rather than performing real-time sensor processing and error correction, significantly reducing operation time
Solution Approach 2:
The patent enables the robot to skip slow sensor processing and iterative error correction by using the pre-computed virtual map for direct position estimation and path planning, thus rushing through the navigation process more efficiently
Data Source
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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.