Research On Full Coverage Path Planning Of Multi-disinfection Robot

Since the outbreak of the outbreak of 2019,the disinfection of public space is especially important,and the research of disinfection robot is becoming more and more attention of scholars from all circles of life,becoming a hot topic in the field of robot research.In order to improve the risk of disinfecting personnel,this paper analyzes the path planning method,full coverage path planning method and multi-robot path planning method,which is often involved in the disinfection robot,and determines the idea of the full coverage path planning of the multi-sterilized robot,and the requirement of the public space disinfection,and the improvement and innovation of the traditional multi-robot total coverage.This paper focuses on the method of single machine,the method of map segmentation,the task distribution method,and the simulation test based on the ros system.The main results and summaries are as follows:Firstly,the paper analyzes the problems of the full coverage path planning of the bioincentive neural network,and the requirements and practical conditions of the evaluation indexes and disinfection of the whole coverage of the anti-disinfection robot are improved,and the original algorithm is improved,so that the robot can be fully sterilized.Based on the bioincentive neural network algorithm,the path correction strategy and the priority algorithm are introduced,and the robot can reduce the number of turns,and reduce the length and time of the path,and improve the efficiency of the work.The obstacle in the map is the high frequency contact area of the actual environment,and the improved algorithm can be strengthened to disinfect the obstacles in order to reduce the risk of the spread of the virus.After the robot is distributed to different robots to implement the subarea coverage,this paper introduces the traditional method of segmentation and the problem of the problem,introduces the extraction method of the direct skeleton,and this paper puts forward a kind of contract segmentation method(cdm),which can make the sub-map of the division more regular,and avoid oversegmentation,and the oversegmentation will bring very large amount of work to the next task distribution.Then,in order to distribute multiple robots to different sub-maps,we built a mission allocation for the disinfection robot.The task allocation of the whole coverage path planning can be compared to the problem of multi-travel business,and the cost function of multiple nonlinear principles is established,which will complete the time of the task,the distance of the journey,the amount of energy,the amount of energy,the cost function of the task distribution,and the task distribution of multi-robot.Finally,in order to verify the feasibility of the scheme and algorithm,a physical experiment platform was built.The hardware system was built based on Turtle Bot3 robot,and the software system was designed based on ROS system.Based on the experimental environment map we built,simulation experiments were carried out on the path planning of full coverage of single disinfection robot and full coverage of multi-disinfection robot.By comparison,the superiority of multi-robot disinfection was verified.Finally,the simulation program is transplanted to Turtle3 robot,and the actual performance of the multi-disinfection robot is verified.