Nonholonomic Robot Field Coverage With Minimum-Radius Lane Linking
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Solution Overview
Problem
Prior art algorithms fail to effectively handle non-holonomic robots with limited turning radius, leading to incomplete field coverage and incorrect path generation due to mislabeled cells and inability to link lanes, especially when transitioning between adjacent cells and navigating around obstacles.
Innovation Solution
The method generates a path for nonholonomic robots to cover a field by using lane linking, cell traversal, and lane wrapping algorithms, ensuring the robot follows a straight line as much as possible while avoiding obstacles and completing tasks efficiently, with the aid of sensors like GPS, RADAR, and LIDAR for navigation and obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If prior art algorithms are used for field coverage, then the robot can navigate the field, but the field coverage is incomplete and incorrect due to inability to handle nonholonomic constraints
Solution Approach 1:
The field is divided into discrete cells that can be individually processed and labeled. This segmentation allows the algorithm to systematically handle each cell's coverage requirements while respecting nonholonomic constraints, ensuring complete and correct field coverage.
Solution Approach 2:
The patent introduces a new dimension of cell labeling that incorporates nonholonomic constraints into the path planning process. By adding this dimensional consideration to traditional field coverage algorithms, the system can generate valid paths for nonholonomic robots while maintaining complete coverage.
2Productivity
If the robot follows straight lines to minimize turns, then coverage efficiency improves, but the robot cannot navigate around obstacles or follow complex boundary shapes
Solution Approach 1:
The path planning algorithm dynamically adjusts the robot's trajectory by introducing turn commands at appropriate locations while maintaining straight-line segments elsewhere. This dynamic path generation allows the robot to efficiently cover the field while adapting to obstacles and boundary constraints.
Solution Approach 2:
The patent uses intermediate cells as mediators to connect straight-line path segments. These intermediate cells provide the necessary turning space for nonholonomic robots to transition between parallel coverage lanes while avoiding obstacles and following boundary shapes.
3Manufacturing precision
If the robot makes tight turns to follow field boundaries and avoid obstacles, then path accuracy improves, but the robot violates minimum turning radius constraints
Solution Approach 1:
The algorithm incorporates curved transition paths with controlled curvature that respect the robot's minimum turning radius. Instead of sharp angular turns, the system generates smooth curved segments that allow the robot to follow field boundaries and avoid obstacles while maintaining reliable constraint satisfaction.
Solution Approach 2:
The path planning algorithm adjusts path geometry parameters (such as turn radius and transition curve length) to ensure they meet the robot's minimum turning radius constraints. By dynamically changing these parameters based on local environmental features, the system maintains both path accuracy and constraint satisfaction.
4Reliability
If the algorithm processes every cell individually to ensure complete coverage, then coverage completeness improves, but computational complexity and processing time increase
Solution Approach 1:
The algorithm merges adjacent cells that share similar coverage characteristics and constraint requirements into processing units. This merging reduces the total number of individual cell processing operations while maintaining complete coverage, thereby lowering computational complexity and processing time.
Solution Approach 2:
The patent develops a universal cell processing framework that handles multiple functions (coverage verification, constraint checking, path generation) in a single integrated algorithm. This multi-functional approach eliminates the need for separate processing steps for each function, reducing overall algorithmic complexity while ensuring complete and correct coverage.
Data Source
AI summary
A software product and methods determine a field coverage method for a nonholonomic robot to process a field using parallel lanes. A cellular decomposition algorithm divides the field into a plurality of cells, each having a plurality of parallel lanes. Permutations of lane processing orders are determined for each cell, based upon a minimum turning radius of the robot. A cell graph is generated to determine a shortest path for single-time processing each lane in each cell without violating the minimum turning radius of the robot. A step list defining movement of the nonholonomic robot along each lane in each cell of the shortest path through the cell graph is generated, and transits between the lanes, and laps around the field and any obstacles are added. A path program to control the nonholonomic robot to process the field is generated based upon the step list.