Robotic Soil Cultivation Path Replanning for Uncovered Grid Points
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Solution Overview
Problem
Existing robotic vehicles for soil cultivation face challenges in maintaining precise position determination and efficient operation in areas with varying soil conditions and obstacles, leading to deviations from planned trajectories and uneven soil cultivation.
Innovation Solution
A robotic vehicle equipped with a controller that uses a discretized coordinate grid system to schedule movement trajectories, detects deviations from planned paths, and adjusts the trajectory to cover uncovered grid points, ensuring efficient and precise soil cultivation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robotic vehicle operates along a scheduled movement trajectory, then the soil cultivation efficiency is improved, but deviations from the planned trajectory occur due to uneven terrain and slope conditions, leading to uncovered grid points
Solution Approach 1:
The controller continuously monitors the actual movement trajectory and compares it with the scheduled trajectory. When deviations are detected that result in uncovered grid points, the system generates feedback to repeat the movable operation in the deviated areas, ensuring complete coverage while maintaining overall cultivation efficiency
Solution Approach 2:
The system pre-identifies uncovered grid points by comparing actual trajectory with scheduled trajectory before completing the cultivation operation. This allows the controller to plan repeat operations specifically for deviated areas, preventing incomplete coverage while minimizing rework
2Manufacturing precision
If the robotic vehicle adjusts its trajectory to cover uncovered grid points, then the trajectory coverage precision is improved, but additional time is required to repeat operations in deviated areas
Solution Approach 1:
The system extracts only the deviated grid points that require repeat operation, rather than reprocessing the entire work area. The controller identifies specific uncovered grid points and generates targeted repeat operations only for those areas, minimizing additional operation time while ensuring complete coverage
Solution Approach 2:
The work area is divided into discrete grid points, allowing the system to identify and process only the specific deviated grid points that require repeat operation. This segmentation enables selective reprocessing of affected areas rather than the entire cultivation zone
Data Source
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AI summary
The invention relates to a robotic vehicle (100) for movable operation in a work area, the movable operation comprising a soil cultivation, the work area being represented by a set of discretized coordinate grid points (112), the vehicle (100) comprising a controller (118), the controller (118) comprising a memory (122) and a processor, the memory (122) comprising instructions (124), wherein execution of the instructions (124) by the processor causes the vehicle (100) for performing the movable operation along a scheduled movement trajectory (130; 410; 1200) of the vehicle (100), the movable operation along the scheduled movement trajectory (130; 410; 1200) covering a set of scheduled grid points of the set of discretized coordinate grid points (112); determining if due to a deviation of the real movement trajectory (150) of the vehicle (100) from the scheduled movement trajectory (130; 410; 1200) deviated grid points (154) representing grid points of the set of scheduled grid points are uncovered by the movable operation along the scheduled movement trajectory (130; 410; 1200); in case deviated grid points (154) are uncovered, repeating the performing of the movable operation and the determination with the scheduled movement trajectory (130; 410; 1200) comprising a new scheduled movement trajectory (156) of the vehicle (100) covering the deviated grid points (154).