Vision-Based Trajectory Adjustment for Boundary-Following Robots
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Solution Overview
Problem
Self-moving devices face challenges in efficiently covering a working region while minimizing repetitive movements and ensuring accurate boundary following and obstacle avoidance, particularly in complex environments.
Innovation Solution
A self-moving device equipped with an image acquisition module and control circuit that recognizes boundaries and obstacles, generating reference lines to adjust its movement trajectory by controlling steering angles based on relative positional relationships, allowing it to maintain a consistent path with the boundary and avoid obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the self-moving device uses traditional path planning methods, then it can cover the working region, but it produces repetitive movements and fails to accurately follow boundaries in complex environments
Solution Approach 1:
The device uses an image acquisition module to continuously capture images of the working region and boundary, feeds this visual information back to a control circuit, and dynamically adjusts the movement trajectory based on the detected boundary position and orientation, eliminating repetitive movements through real-time feedback control
Solution Approach 2:
The path planning system transitions from static pre-programmed paths to dynamic adaptive trajectory adjustment, where the movement path is continuously optimized based on real-time boundary detection and image processing results
2Measurement precision
If the self-moving device increases navigation complexity to improve boundary following accuracy, then it can follow boundaries more precisely, but the device complexity increases
Solution Approach 1:
The patent replaces complex mechanical navigation systems with vision-based boundary detection using an image acquisition module and control circuit that processes visual information to determine boundary position and orientation, achieving high precision through software-based image processing rather than mechanical complexity
Solution Approach 2:
The image acquisition module serves as an intermediary between the physical boundary and the control system, converting physical boundary information into visual data that the control circuit can process to generate accurate trajectory adjustments
3Device complexity
If the self-moving device uses simple navigation, then the device complexity is low, but it cannot accurately return along the boundary or avoid obstacles in complex environments
Solution Approach 1:
The control circuit continuously receives visual feedback from the image acquisition module about boundary position and orientation, dynamically adjusting the movement trajectory to ensure accurate boundary following and reliable obstacle avoidance through real-time feedback control
Data Source
AI summary
This application discloses a self-moving device, a method for adjusting a movement trajectory. The device includes a body, an image acquisition module, and a control circuit. The image acquisition module acquires an image in a traveling direction of the body. The control circuit fits, according to the image, a boundary corresponding to a working region in which the self-moving device is located. In response to the body moves toward the boundary and the body and the boundary meet a preset distance relationship, an angle relationship between the traveling direction of the body and the boundary is recognized according to the image, and the body is controlled to steer.