{"title":"利用遗传算法设计双点接触爬梯机器人并对其进行多目标优化","authors":"Darshita Shah, Jatin Dave, Mihir Chauhan, Vijay Ukani, Suhani Patel","doi":"10.1002/rob.22403","DOIUrl":null,"url":null,"abstract":"<p>This paper presents the design and optimization of a climbing robot. The design of a ladder-climbing robot is done with fundamental mathematical considerations. The designed robot is robust enough to manage all environmental calamities, and at the same time, it is optimized for lightweight to reduce the actuator's cost and ease of transportation. An analytical evaluation is carried out for both static and dynamic conditions to determine strength and motion characteristics. The multiobjective optimization of the design parameters of a ladder-climbing robot is done to obtain optimized values of design parameters. The formulation of an optimization problem that considers the minimization of weight and natural frequency is performed. Using an evolutionary genetic algorithm (GA) for the multicriteria optimization problem is solved, and a Pareto front solution is obtained. The optimal values of the parameters are decided based on the knee selection technique. As both objective functions are contradictory, the optimum results significantly improve the robot's performance. Controlling the proportional–integral–derivative (PID) parameters is crucial as the robot climbs with a two-point contact gait pattern. The controlling parameters impart stability to the robot. PID parameters like proportional, integral and derivative gain are tunned using the GA. Finally, the developed prototype is tested on the ladders of the tower, and satisfactory climbing motion is achieved.</p>","PeriodicalId":192,"journal":{"name":"Journal of Field Robotics","volume":"42 1","pages":"219-241"},"PeriodicalIF":4.2000,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design and multiobjective optimization of a two-point contact ladder-climbing robot using a genetic algorithm\",\"authors\":\"Darshita Shah, Jatin Dave, Mihir Chauhan, Vijay Ukani, Suhani Patel\",\"doi\":\"10.1002/rob.22403\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper presents the design and optimization of a climbing robot. The design of a ladder-climbing robot is done with fundamental mathematical considerations. The designed robot is robust enough to manage all environmental calamities, and at the same time, it is optimized for lightweight to reduce the actuator's cost and ease of transportation. An analytical evaluation is carried out for both static and dynamic conditions to determine strength and motion characteristics. The multiobjective optimization of the design parameters of a ladder-climbing robot is done to obtain optimized values of design parameters. The formulation of an optimization problem that considers the minimization of weight and natural frequency is performed. Using an evolutionary genetic algorithm (GA) for the multicriteria optimization problem is solved, and a Pareto front solution is obtained. The optimal values of the parameters are decided based on the knee selection technique. As both objective functions are contradictory, the optimum results significantly improve the robot's performance. Controlling the proportional–integral–derivative (PID) parameters is crucial as the robot climbs with a two-point contact gait pattern. The controlling parameters impart stability to the robot. PID parameters like proportional, integral and derivative gain are tunned using the GA. Finally, the developed prototype is tested on the ladders of the tower, and satisfactory climbing motion is achieved.</p>\",\"PeriodicalId\":192,\"journal\":{\"name\":\"Journal of Field Robotics\",\"volume\":\"42 1\",\"pages\":\"219-241\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Field Robotics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/rob.22403\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Field Robotics","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/rob.22403","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
摘要
本文介绍了爬梯机器人的设计和优化。爬梯机器人的设计基于基本的数学考虑。所设计的机器人坚固耐用,足以应对各种环境灾害,同时还对其轻量化进行了优化,以降低执行器的成本并方便运输。对静态和动态条件进行了分析评估,以确定强度和运动特性。对爬梯机器人的设计参数进行了多目标优化,以获得设计参数的优化值。优化问题的制定考虑了重量和固有频率的最小化。使用进化遗传算法(GA)解决多标准优化问题,并获得帕累托前沿解。参数的最佳值是根据膝选择技术决定的。由于两个目标函数是相互矛盾的,最优结果大大提高了机器人的性能。控制比例积分派生(PID)参数至关重要,因为机器人以两点接触的步态爬行。控制参数可增强机器人的稳定性。PID参数,如比例、积分和导数增益,可通过 GA 进行调整。最后,在塔梯上对开发的原型进行了测试,结果令人满意。
Design and multiobjective optimization of a two-point contact ladder-climbing robot using a genetic algorithm
This paper presents the design and optimization of a climbing robot. The design of a ladder-climbing robot is done with fundamental mathematical considerations. The designed robot is robust enough to manage all environmental calamities, and at the same time, it is optimized for lightweight to reduce the actuator's cost and ease of transportation. An analytical evaluation is carried out for both static and dynamic conditions to determine strength and motion characteristics. The multiobjective optimization of the design parameters of a ladder-climbing robot is done to obtain optimized values of design parameters. The formulation of an optimization problem that considers the minimization of weight and natural frequency is performed. Using an evolutionary genetic algorithm (GA) for the multicriteria optimization problem is solved, and a Pareto front solution is obtained. The optimal values of the parameters are decided based on the knee selection technique. As both objective functions are contradictory, the optimum results significantly improve the robot's performance. Controlling the proportional–integral–derivative (PID) parameters is crucial as the robot climbs with a two-point contact gait pattern. The controlling parameters impart stability to the robot. PID parameters like proportional, integral and derivative gain are tunned using the GA. Finally, the developed prototype is tested on the ladders of the tower, and satisfactory climbing motion is achieved.
期刊介绍:
The Journal of Field Robotics seeks to promote scholarly publications dealing with the fundamentals of robotics in unstructured and dynamic environments.
The Journal focuses on experimental robotics and encourages publication of work that has both theoretical and practical significance.