Robot Passage Navigation Using Coordinate Rotation and Azimuth Control
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Solution Overview
Problem
Existing robot navigation technologies face challenges in accurately planning paths through complex and narrow passages due to environmental conditions and sensor errors, leading to reduced safety and accuracy in robot travel.
Innovation Solution
A robot traveling method that involves detecting obstacles using a laser radar, performing coordinate system transformation to obtain accurate obstacle positions relative to the robot, determining the farthest reachable points, and adjusting the robot's azimuth to ensure safe passage through narrow passages by controlling the robot's travel based on target azimuth deviations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robot navigation uses conventional path planning methods, then the robot can move through the environment, but the safety and accuracy are reduced due to environmental conditions and sensor errors in narrow passages
Solution Approach 1:
The patent performs preliminary coordinate system transformations and azimuth calculations before the robot executes movement. By pre-computing the target azimuth deviation and farthest reachable points based on current obstacle positions, the robot can adjust its path in advance, compensating for potential positioning errors before they affect navigation accuracy and safety in narrow passages.
Solution Approach 2:
The patent implements a feedback mechanism where the robot continuously detects obstacles, transforms their coordinates to the robot's coordinate system, calculates target azimuth deviations, and adjusts its movement accordingly. This closed-loop control allows the robot to compensate for environmental conditions and sensor errors by constantly comparing actual obstacle positions with planned paths and making real-time corrections.
2Measurement precision
If the robot performs detailed coordinate transformation and azimuth calculation for every obstacle point, then navigation accuracy improves, but computational complexity increases
Solution Approach 1:
The patent segments the obstacle detection and path planning process into distinct steps: detecting obstacles and obtaining first coordinate points in the obstacle detector's coordinate system, transforming to second coordinate points in the robot's coordinate system, calculating azimuths for each point, determining farthest reachable points, and computing target azimuth deviation. This segmentation allows the complex navigation problem to be solved through a series of manageable computational steps, reducing overall complexity while maintaining precision.
Solution Approach 2:
The patent performs coordinate axis rotation on all second coordinate points based on the currently traversed first azimuth. By rotating the coordinate system to align with the current azimuth direction, the complex 2D spatial relationship problem is transformed into a simpler 1D distance calculation problem along the rotated axis, making it easier to determine the farthest reachable point and calculate target azimuth deviation with reduced computational effort.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the safety and accuracy of robot travel in narrow passages by compensating for environmental and sensor errors, allowing the robot to navigate along the passage's midline effectively, thus improving robustness and avoiding collisions.
Implementation Method 1
detecting an obstacle, and obtaining first coordinate points of the detected obstacle in a first coordinate system, in which the first coordinate system is a coordinate system of an obstacle detector
Data Source
AI summary
A robot traveling method, includes: detecting an obstacle, and obtaining first coordinate points of the obstacle in a first coordinate system which is a coordinate system of an obstacle detector; obtaining second coordinate points of the obstacle in a second coordinate system by performing coordinate system transformation on the first coordinate points, the second coordinate system being a coordinate system of a robot; obtaining a first azimuth corresponding to each second coordinate point, traversing all the first azimuths, and determining a farthest target coordinate point that the robot is allowed to reach when walking along a currently traversed first azimuth by performing coordinate axis rotation on all the second coordinate points based on the currently traversed first azimuth; and obtaining a target azimuth deviation of the robot based on the target coordinate point corresponding to each first azimuth, and controlling the robot to travel based on the target azimuth deviation.