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CLC number: TP242.6

On-line Access: 2023-02-27

Received: 2022-05-15

Revision Accepted: 2022-07-22

Crosschecked: 2023-02-27

Cited: 0

Clicked: 1341

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Caihong LI

https://orcid.org/0000-0003-0255-9249

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Frontiers of Information Technology & Electronic Engineering  2023 Vol.24 No.2 P.231-244

http://doi.org/10.1631/FITEE.2200211


Parameter value selection strategy for complete coverage path planning based on the Lü system to perform specific types of missions


Author(s):  Caihong LI, Cong LIU, Yong SONG, Zhenying LIANG

Affiliation(s):  School of Computer Science and Technology, Shandong University of Technology, Zibo 255000, China; more

Corresponding email(s):   lich@sdut.edu.cn

Key Words:  Chaotic mobile robot, Lü, system, Complete coverage path planning (CCPP), Parameter value selection strategy, Lyapunov exponent, Pearson correlation coefficient


Caihong LI, Cong LIU, Yong SONG, Zhenying LIANG. Parameter value selection strategy for complete coverage path planning based on the Lü system to perform specific types of missions[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(2): 231-244.

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Abstract: 
We propose a novel parameter value selection strategy for the ; system to construct a chaotic robot to accomplish the complete coverage path planning (CCPP) task. The algorithm can meet the requirements of high randomness and coverage rate to perform specific types of missions. First, we roughly determine the value range of the parameter of the ; system to meet the requirement of being a dissipative system. Second, we calculate the lyapunov exponents to narrow the value range further. Next, we draw the phase planes of the system to approximately judge the topological distribution characteristics of its trajectories. Furthermore, we calculate the pearson correlation coefficient of the variable for those good ones to judge its random characteristics. Finally, we construct a chaotic robot using variables with the determined parameter values and simulate and test the coverage rate to study the relationship between the coverage rate and the random characteristics of the variables. The above selection strategy gradually narrows the value range of the system parameter according to the randomness requirement of the coverage trajectory. Using the proposed strategy, proper variables can be chosen with a larger lyapunov exponent to construct a chaotic robot with a higher coverage rate. Another chaotic system, the Lorenz system, is used to verify the feasibility and effectiveness of the designed strategy. The proposed strategy for enhancing the coverage rate of the mobile robot can improve the efficiency of accomplishing CCPP tasks under specific types of missions.

基于Lü系统的移动机器人完成特殊情况下全覆盖路径规划的参数值选择策略

李彩虹1,刘聪1,宋勇2,梁振英1
1山东理工大学计算机科学与技术学院,中国淄博市,255000
2山东大学(威海)机电与信息工程学院,中国威海市,264209
摘要:针对移动机器人完成特殊情况下的全覆盖路径规划(complete coverage path planning, CCPP)任务,基于Lü系统,提出一种构造混沌机器人的系统参数值综合选择策略,以满足特殊任务下遍历轨迹高随机性和高覆盖率的需求。首先利用混沌系统必为耗散系统的特点,大致确定Lü系统成为耗散系统的参数取值范围;然后计算耗散系统下的李雅普诺夫指数谱,缩小系统参数的取值范围;其次画出这些参数下的相平面,大致判断其轨迹的拓扑分布特性;进一步在好的参数取值里,计算每个参数下变量的皮尔逊相关系数,判断每个变量的随机特性。最后,在所确定参数值下,利用其中的变量构造混沌机器人,并仿真测试了覆盖率,研究覆盖率和变量随机特性之间的关系。上述综合选择策略根据覆盖轨迹混沌性和随机性的要求,逐渐缩小了系统参数的取值范围。与使用一组固定的经典参数值的Lü系统相比,经过综合方法选择参数值的系统,能挑选出李雅普诺夫指数大的变量来构造混沌机器人,从而使覆盖轨迹的随机性能更高。另一个混沌Lorenz系统,用来测试和验证所设计策略的可行性和有效性。此类研究能够提高机器人完成特殊情况下CCPP任务的效率。

关键词:混沌移动机器人;Lü系统;全覆盖路径规划;参数值选择策略;李雅普诺夫指数;皮尔逊相关系数

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Reference

[1]Curiac DI, Volosencu C, 2009. Developing 2D chaotic trajectories for monitoring an area with two points of interest. Proc 10th WSEAS Int Conf on Automation & Information, p.366-369.

[2]Curiac DI, Volosencu C, 2012. Chaotic trajectory design for monitoring an arbitrary number of specified locations using points of interest. Math Probl Eng, 2012:‍940276.

[3]Curiac DI, Volosencu C, 2014. A 2D chaotic path planning for mobile robots accomplishing boundary surveillance missions in adversarial conditions. Commun Nonl Sci Numer Simul, 19(10):3617-3627.

[4]Curiac DI, Volosencu C, 2015. Imparting protean behavior to mobile robots accomplishing patrolling tasks in the presence of adversaries. Bioinspir Biomim, 10(5):056017.

[5]Curiac DI, Banias O, Volosencu C, et al., 2018. Novel bioinspired approach based on chaotic dynamics for robot patrolling missions with adversaries. Entropy, 20(5):378.

[6]Fahmy AA, 2012. Performance evaluation of chaotic mobile robot controllers. Int Trans J Eng Manag Appl Sci Technol, 3(2):‍145-158.

[7]Galceran E, Carreras M, 2013. A survey on coverage path planning for robotics. Robot Auton Syst, 61(12):‍‍1258-1276.

[8]Hoshino S, Takahashi K, 2019. Dynamic partitioning strategies for multi-robot patrolling systems. J Robot Mechatr, 31(4):535-545.

[9]Huang KC, Lian FL, Chen CT, et al., 2021. A novel solution with rapid Voronoi-based coverage path planning in irregular environment for robotic mowing systems. Int J Intell Robot Appl, 5(4):558-575.

[10]Lakshmanan AK, Mohan RE, Ramalingam B, et al., 2020. Complete coverage path planning using reinforcement learning for Tetromino based cleaning and maintenance robot. Autom Constr, 112:103078.

[11]Li CH, Song Y, Wang FY, et al., 2015. Chaotic path planner of autonomous mobile robots based on the standard map for surveillance missions. Math Probl Eng, 2015:‍263964.

[12]Li CH, Song Y, Wang FY, et al., 2016. A bounded strategy of the mobile robot coverage path planning based on Lorenz chaotic system. Int J Adv Robot Syst, 13:107.

[13]Li CH, Song Y, Wang FY, et al., 2017. A chaotic coverage path planner for the mobile robot based on the Chebyshev map for special missions. Front Inform Technol Electron Eng, 18(9):1305-1319.

[14]Li CH, Wang ZQ, Fang C, et al., 2018. An integrated algorithm of CCPP task for autonomous mobile robot under special missions. Int J Comput Intell Syst, 11(1):‍1357-1368.

[15]Li CH, Fang C, Wang FY, et al., 2019. Complete coverage path planning for an Arnold system based mobile robot to perform specific types of missions. Front Inform Technol Electron Eng, 20(11):1530-1542.

[16]Liu P, Sun JJ, Qin HZ, et al., 2017. The area-coverage path planning of a novel memristor-based double-stroll chaotic system for autonomous mobile robots. Chinese Automation Congress, p.6982-6987.

[17]Lorenz EN, 1997. The Essence of Chaos. Liu SD, translator. China Meteorological Press, Beijing, China, p.‍186-189(in Chinese).

[18]Lü JH, Chen GR, 2002. A new chaotic attractor coined. Int J Bifurc Chaos, 12(3):659-661.

[19]Martins-Filho LS, Macau EEN, 2007. Trajectory planning for surveillance missions of mobile robots. In: Mukhopadhyay SC, Sen Gupta G (Eds.), Autonomous Robots and Agents. Studies in Computational Intelligence. Springer, Berlin, Heidelberg, Germany, p.109-117.

[20]Mehdi SA, Kareem RS, 2017. Using fourth-order Runge-Kutta method to solve Lü chaotic system. Am J Eng Res, 6(1):72-77.

[21]Moysis L, Petavratzis E, Volos C, et al., 2020. A chaotic path planning generator based on logistic map and modulo tactics. Robot Auton Syst, 124:103377.

[22]Moysis L, Rajagopal K, Tutueva AV, et al., 2021. Chaotic path planning for 3D area coverage using a pseudo-random bit generator from a 1D chaotic map. Mathematics, 9(15):1821.

[23]Nakamura Y, Sekiguchi A, 2001. The chaotic mobile robot. IEEE Trans Robot Autom, 17(6):898-904.

[24]Peitgen HO, Jürgens H, Saupe D, 2004. Chaos and Fractals: New Frontiers of Science (2nd Ed.. Springer, New York, USA.

[25]Petavratzis E, Moysis L, Volos C, et al., 2020. Chaotic path planning for grid coverage using a modified Logistic-may map. J Autom Mob Robot Intell Syst, 14(2):3-9.

[26]Prado J, Marques L, 2014. Energy efficient area coverage for an autonomous demining robot. In: Armada MA, Sanfeliu A, Ferre M (Eds.), ROBOT2013: First Iberian Robotics Conf: Advances in Intelligent Systems and Computing. Springer International Publishing, Switzerland, p.‍459-471.

[27]Profillidis VA, Botzoris GN, 2019. Statistical methods for transport demand modeling. In: Profillidis VA, Botzoris GN (Eds.), Modeling of Transport Demand. Elsevier, Amsterdam, the Netherlands, p.163-224.

[28]Rabah K, Ladaci S, Lashab M, 2018. Bifurcation-based fractional-order PIλDμ controller design approach for nonlinear chaotic systems. Front Inform Technol Electron Eng, 19(2):180-191.

[29]Rajagopal K, Bayani A, Jafari S, et al., 2020. Chaotic dynamics of a fractional order glucose-insulin regulatory system. Front Inform Technol Electron Eng, 21(7):1108-1118.

[30]Sekiguchi A, Nakamura Y, 1999. The chaotic mobile robot. IEEE/RSJ Int Conf on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients, p.172-178.

[31]Volos CK, Kyprianidis IM, Stouboulos IN, 2012a. A chaotic path planning generator for autonomous mobile robots. Robot Auton Syst, 60(4):651-656.

[32]Volos CK, Bardis NG, Kyprianidis IM, et al., 2012b. Implementation of mobile robot by using double-scroll chaotic attractors. Proc 11th Int Conf on Applications of Electrical and Computer Engineering, p.119-124.

[33]Volos CK, Kyprianidis IM, Stouboulos IN, 2012c. Motion control of robots using a chaotic truly random bits generator. J Eng Sci Technol Rev, 5(2):6-11.

[34]Volos CK, Kyprianidis IM, Stouboulos IN, 2013. Experimental investigation on coverage performance of a chaotic autonomous mobile robot. Robot Auton Syst, 61(12):1314-1322.

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