Patrol Path Planning Using Directed Graph Coverage Metrics
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Solution Overview
Problem
Current patrol path planning methods for security robots lack integration with geographical features and do not effectively utilize graph-based planning, leading to inefficient patrols and increased risks of invasion and property loss.
Innovation Solution
A patrol device and method that utilize a directed graph to plan patrol paths based on Average Patrol Omission (APO) and Average Patrol Quality (APQ) values, employing algorithms like Shortest Path Permutation Method (SPPM) and Locally Optimum Repetitious Method (LORM) to select optimal paths, ensuring efficient and effective coverage of patrol regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional patrol path planning methods (Potential Field, MDP, TSP, VRP) are used, then robots can perform basic patrol functions, but the patrol efficiency is low and cannot effectively reduce invasion risks
Solution Approach 1:
The patent transforms the patrol path planning problem by changing the representation parameters from traditional coordinate-based or graph-edge-based methods to a graph-node-based coverage model. Patrol regions are defined as nodes in a directed graph, and the planning algorithm optimizes the sequence of visiting these nodes to maximize coverage while minimizing omission, thereby simultaneously improving patrol efficiency and reliability.
Solution Approach 2:
The patrol area is segmented into multiple discrete patrol regions (nodes), each representing a specific zone that needs to be monitored. This segmentation allows the system to independently evaluate and optimize coverage for each region while maintaining overall patrol efficiency through graph-based path planning that connects these regions optimally.
2Reliability
If comprehensive coverage of all patrol regions is achieved, then patrol quality improves, but patrol time and path length increase
Solution Approach 1:
The patent introduces dynamic adjustment mechanisms where the patrol path planning can be adapted based on real-time conditions. The system dynamically selects which patrol regions to visit next based on current coverage status, allowing flexible optimization between comprehensive coverage and time efficiency. The graph-based model enables dynamic re-planning when new information becomes available.
Solution Approach 2:
The patent acknowledges that complete coverage of all patrol regions may not always be necessary or efficient. The system allows for partial coverage strategies where high-priority regions are visited frequently while lower-priority regions are visited less often, achieving acceptable patrol quality without excessive time investment. The graph model supports prioritizing critical nodes in the patrol sequence.
3Device complexity
If fixed patrol paths are used, then path planning is simple, but the system cannot adapt to changing security conditions or optimize long-term patrol strategies
Solution Approach 1:
The patent implements feedback mechanisms where patrol outcomes are evaluated and used to improve future patrol planning. The system tracks which regions have been covered, identifies omissions, and uses this information to adjust subsequent patrol paths. This feedback loop enables the system to learn from past patrols and adapt to changing security conditions while maintaining manageable complexity through the structured graph model.
Solution Approach 2:
The patent performs preliminary analysis of the patrol area to construct the directed graph model before actual patrol execution. By pre-processing the environment information and establishing the graph structure with defined nodes and transitions, the system prepares adaptive capabilities in advance, allowing for efficient real-time decision-making during patrol without requiring complex on-the-fly calculations.
Data Source
AI summary
The present invention relates to a patrol device and a patrol path planning method. The patrol device includes an operating unit configured to establish a plurality of patrol paths, each of which has an Average Patrol Omission (APO) value and an Average Patrol Quality (APQ) value, and to determine an optimum patrol path from the plurality of patrol paths according to the APO value and the APQ value; and a moving unit configured to move along the optimum patrol path. The method includes providing a plurality of patrol paths, each of which has an Average Patrol Omission (APO) value and an Average Patrol Quality (APQ) value; and evaluating the plurality of patrol paths according to the respective APO values and the respective APQ values so as to select an optimum patrol path therefrom.