Robot Path Fusion Planning for Narrow Obstacle Channels
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Solution Overview
Problem
Conventional path search algorithms fail to navigate robots through narrow channels effectively due to sensor errors and map inaccuracies, which lead to incorrect obstacle markings and blocked paths in grid maps.
Innovation Solution
A path fusion and planning method that sets navigation starting and ending points, performs neighborhood searches, and uses a cache space to store nodes for tracing back paths, allowing the robot to bypass obstacles and plan routes through narrow channels by integrating heuristic search algorithms with candidate routes that satisfy specific conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional path search algorithms are used in grid maps, then the path planning can be implemented, but the narrow channels are incorrectly marked as obstacles due to sensor errors and map inaccuracies, causing navigation failure
Solution Approach 1:
The patent performs preliminary actions by pre-searching for candidate routes through narrow channels before actual navigation, storing these routes and their endpoints in advance. When navigation is needed, the system directly utilizes these pre-computed routes instead of searching from scratch, ensuring that even if map markings are inaccurate, the pre-verified candidate routes can guide successful navigation through narrow channels.
Solution Approach 2:
The patent introduces an intermediary mechanism by adding a candidate route search and verification module between the standard path search algorithm and the final path selection. This intermediary pre-explores narrow channels, identifies passable routes despite map errors, and provides candidate routes to the path search algorithm, thereby mediating the conflict between map inaccuracies and navigation reliability.
2Productivity
If the robot navigates through narrow channels, then the path coverage is improved, but the sensor errors and accumulated positioning errors cause the narrow channels to be marked as occupied areas, blocking the path
Solution Approach 1:
The system performs preliminary exploration of narrow channels before formal navigation, storing candidate routes and their endpoints in advance. This preliminary action allows the robot to identify passable narrow channels and record their geometries beforehand, so that even when positioning errors occur during actual navigation, the pre-stored candidate routes can be used to successfully traverse these narrow passages.
Solution Approach 2:
The patent creates a copy mechanism by storing candidate route information (coordinates, endpoints, intermediate points) separately from the main grid map. This copied route information serves as an alternative reference that is independent of the potentially erroneous grid map markings, allowing the robot to follow the copied route coordinates even when the grid map incorrectly marks narrow channels as obstacles.
3Loss of time
If heuristic search algorithms are used for path planning, then the search efficiency is improved, but the algorithms fail to bypass obstacles when narrow channels are incorrectly marked as occupied grids
Solution Approach 1:
The patent performs preliminary search actions by pre-computing candidate routes through narrow channels and storing them before actual path planning is needed. This preliminary computation includes identifying endpoints, storing intermediate points, and verifying passability. When the heuristic search algorithm runs, it can directly utilize these pre-computed candidate routes, avoiding the need to re-search through incorrectly marked obstacles, thus maintaining both efficiency and reliability.
Solution Approach 2:
The patent applies local quality by treating narrow channel regions differently from general areas. Instead of applying the standard heuristic search uniformly across the entire map, the system identifies narrow channel locations and pre-computes candidate routes specifically for these regions, storing local route information that can be quickly retrieved during path planning, thereby improving both local navigation reliability and overall search efficiency.
Data Source
AI summary
A path fusing and planning method for a passing region, a robot, and a chip. The robot searches for candidate paths for fusion in a narrow channel having many obstacles distributed therein in advance, and then uses a path fusing and planning method to fuse a heuristic search algorithm and the candidate routes satisfying a search condition, so as to plan an overall navigation path.