Robot Obstacle-Crossing Termination Using Inflection Point Guidance
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Solution Overview
Problem
Conventional visual sweeping robots face reduced success rates and navigation efficiency when crossing obstacles due to inaccurate map markings and precision issues, causing them to deviate from the navigation path and get stuck along obstacle edges.
Innovation Solution
A method for determining obstacle-crossing termination by selecting a target inflection point set from a preset navigation path, calculating distances, and checking if the obstacle is marked on a line segment connecting the inflection point and the robot's current position, allowing the robot to terminate or continue the crossing based on these conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot walks along the edge of the obstacle according to the pre-planned shortest predicted path, then the robot can cross the obstacle, but the robot may get stuck and navigate endlessly around the obstacle due to inaccurate map markings and precision issues
Solution Approach 1:
The patent implements a feedback mechanism by continuously monitoring the robot's position relative to the obstacle and comparing it with the pre-planned shortest predicted path. The system uses real-time detection of whether the robot is still on the predicted path or has deviated due to map inaccuracies or precision issues. When deviation is detected, the system provides feedback to adjust the navigation path, ensuring the robot can successfully cross the obstacle without getting stuck in endless loops.
Solution Approach 2:
The navigation system dynamically adjusts the robot's path based on real-time conditions. Instead of rigidly following a pre-planned path, the system allows dynamic modification of the navigation route when the robot detects deviation from the predicted path. This dynamic adjustment enables the robot to adapt to map inaccuracies and precision issues, maintaining reliable obstacle crossing while minimizing navigation time.
2Productivity
If the robot follows the pre-planned shortest predicted path along the edge, then the robot can potentially cross the obstacle efficiently, but the navigation path accuracy decreases due to map precision issues
Solution Approach 1:
The system performs preliminary action by pre-planning the shortest predicted path along the obstacle edge before the robot starts navigation. This pre-planned path serves as a guide for efficient obstacle crossing. The system prepares the optimal route in advance, allowing the robot to follow a predetermined efficient path while having the capability to adjust if precision issues arise during execution.
Solution Approach 2:
The system changes navigation parameters dynamically based on the robot's actual position and the pre-planned path. When the robot detects that it has deviated from the predicted path due to map precision issues or navigation errors, the system adjusts path parameters to realign with the intended route. This parameter adjustment maintains navigation efficiency while compensating for precision losses.
3Measurement precision
If the robot continuously checks for obstacle crossing termination, then the navigation accuracy improves, but the computational complexity and processing time increase
Solution Approach 1:
The system extracts the key decision-making function from continuous complex calculations by isolating the specific check for obstacle crossing termination. Instead of continuously computing complex path optimization algorithms, the system extracts a simplified check: whether the robot is still on the pre-planned shortest predicted path or has successfully crossed the obstacle. This extraction maintains high detection accuracy while significantly reducing computational complexity.
Data Source
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AI summary
A method for determining a termination of an obstacle-crossing, a method for controlling an obstacle-crossing control, a chip, and a robot. The obstacle-crossing termination determination method includes: when a robot walks along an edge according to a pre-planned shortest predicted path along the edge, selecting a second preset inflection point set, which meets a guiding condition, from a preset navigation path; an optimal inflection point is acquired from the second preset inflection point set, which meets the guiding condition; whether an obstacle is marked on a line segment which connects the optimal inflection point to the current position of the robot is determined; if so, the current obstacle crossing performed by the robot is not determined to be terminated ; otherwise, the current obstacle crossing performed by the robot is determined to be terminated.