Warehousing Robot Obstacle Avoidance with Dynamic Detection Regions
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Solution Overview
Problem
Existing obstacle avoidance methods for warehousing robots are ineffective due to environmental constraints and interference from ambient light, leading to poor collision avoidance performance.
Innovation Solution
An obstacle avoidance method and apparatus that dynamically determines detection regions based on working state information, including working mode and region, to adjust detection shapes and sizes according to current running speed, thereby improving collision avoidance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If infrared scanner is used for obstacle avoidance, then the obstacle avoidance device can detect obstacles, but the obstacle avoidance effect is poor due to ambient light interference
Solution Approach 1:
The patent changes the detection parameter from infrared wavelength to blue light wavelength (450-480nm). This parameter change makes the detection less sensitive to ambient light interference while maintaining obstacle detection capability, thereby improving reliability under varying lighting conditions
Solution Approach 2:
The patent implements dynamic adjustment of detection region range based on robot speed. When speed exceeds a threshold, the detection range is reduced to prioritize forward path detection, adapting the system behavior to current operating conditions to maintain effective obstacle avoidance
2Area of stationary object
If detection region range is increased to improve obstacle detection coverage, then more obstacles can be detected, but detection precision for specific directions decreases
Solution Approach 1:
The patent dynamically adjusts the detection region range based on robot speed. When speed is high, the detection range is reduced to concentrate detection resources on the forward path, improving precision where needed. When speed is low, the detection range is expanded to provide broader coverage, resolving the contradiction between coverage and precision
Solution Approach 2:
The patent applies different detection region configurations to different working modes (linear vs. rotation). In linear mode, a focused forward detection region is used for precision. In rotation mode, a broader circular region is used for comprehensive coverage, allowing each local context to have optimized detection quality
Data Source
AI summary
An obstacle avoidance method and apparatus, and a warehousing robot. The method includes: obtaining working state information, where the working state information includes a working mode and a working region; determining a detection region according to the working state information; and performing braking if an obstacle exists in the detection region.