Full Text:   <479>

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CLC number: TP242.6

On-line Access: 2019-12-10

Received: 2018-10-14

Revision Accepted: 2019-01-17

Crosschecked: 2019-09-04

Cited: 0

Clicked: 1148

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Cai-hong Li

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

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Frontiers of Information Technology & Electronic Engineering  2019 Vol.20 No.11 P.1530-1542

http://doi.org/10.1631/FITEE.1800616


Complete coverage path planning for an Arnold system based mobile robot to perform specific types of missions


Author(s):  Cai-hong Li, Chun Fang, Feng-ying Wang, Bin Xia, Yong Song

Affiliation(s):  College 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]> Contraction transformation, Complete coverage path planning, Candidate set


Cai-hong Li, Chun Fang, Feng-ying Wang, Bin Xia, Yong Song. Complete coverage path planning for an Arnold system based mobile robot to perform specific types of missions[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(11): 1530-1542.

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Abstract: 
We propose a contraction transformation algorithm to plan a complete coverage trajectory for a mobile robot to accomplish specific types of missions based on the Arnold dynamical system. First, we construct a chaotic mobile robot by combining the variable z of the Arnold equation and the kinematic equation of the robot. Second, we construct the candidate sets including the initial points with a relatively high coverage rate of the constructed mobile robot. Then the trajectory is contracted to the current position of the robot based on the designed contraction transformation strategy, to form a continuous complete coverage trajectory to execute the specific types of missions. Compared with the traditional method, the designed algorithm requires no obstacle avoidance to the boundary of the given workplace, possesses a high coverage rate, and keeps the chaotic characteristics of the produced coverage trajectory relatively unchanged, which enables the robot to accomplish special missions with features of completeness, randomness, or unpredictability.

特殊任务下基于Arnold系统的移动机器人全覆盖路径规划

摘要:基于Arnold动力学系统,提出一种压缩变换方法进行特殊任务下的移动机器人全覆盖路径规划。首先,将Arnold系统中的z变量与机器人运动学方程结合,构造混沌机器人。其次,利用混沌机器人中能够产生较高覆盖率的初始值构造候选集。然后,根据设计的收缩变换方法将轨迹收缩到机器人当前位置,形成连续全覆盖轨迹,以执行特殊任务。与传统方法相比,该算法不需要对给定工作场所的边界进行避障,具有较高覆盖率,且产生的覆盖轨迹混沌特性基本不变,使机器人能够以全覆盖、随机或不可预测的规划路径完成特殊任务。

关键词:混沌机器人;Arnold动力学系统;压缩变换;全覆盖遍历路径;候选集

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Banerjee C, Datta D, Agarwal A, 2015. Chaotic patrol robot with frequency constraints. Proc IEEE Int Conf on Research in Computational Intelligence and Communication Networks, p.340-344.

[2]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.

[3]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.

[4]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.

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

[6]Curiac DI, Volosencu C, 2015b. Path planning algorithm based on Arnold cat map for surveillance UAVs. Def Sci J, 65(6):483-488.

[7]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.

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

[9]Galceran E, Carreras M, 2013. Planning coverage paths on bathymetric maps for in-detail inspection of the ocean floor. Proc Int Conf on Robotics and Automation, p.4159- 4164.

[10]Hwang KS, Lin JL, Huang HL, 2011. Dynamic patrol planning in a cooperative multi-robot system. Proc 14th FIRA RoboWorld Congress on Next Wave in Robotics, p.116- 123.

[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(3):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, 11:1357-1368.

[15]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. Proc Chinese Automation Congress, p.6982-6987.

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

[17]Martins-Filho LS, Macau EEN, 2007a. Patrol mobile robots and chaotic trajectories. Math Probl Eng, 2007:61543.

[18]Martins-Filho LS, Macau EEN, 2007b. Trajectory planning for surveillance missions of mobile robots. In: Mukhopadhyay SC, Gupta GS (Eds.), Autonomous Robots and Agents. Springer Berlin Heidelberg, p.109-117.

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

[20]Oksanen T, Visala A, 2009. Coverage path planning algorithms for agricultural field machines. J Field Robot, 26(8):651- 668.

[21]Ousingsawat J, Earl MG, 2007. Modified lawn-mower search pattern for areas comprised of weighted regions. Proc American Control Conf, p.918-923.

[22]Park E, Kim KJ, del Pobil P, 2012. Energy efficient complete coverage path planning for vacuum cleaning robots. In: Park JJ, Leung VCM, Wang CL, et al. (Eds.), Future Information Technology, Application, and Service. Springer, Dordrecht, p.23-31.

[23]Peitgen HO, Jürgens H, Saupe D, 2004. Chaos and Fractals: New Frontiers of Science. Springer, New York, NY.

[24]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. Springer, Cham, p.459-471.

[25]Sekiguchi A, Nakamura Y, 1999. The chaotic mobile robot. Proc IEEE/RJS Int Conf on Intelligent Robots and Systems, p.172-178.

[26]Sooraska P, Klomkarn K, 2010. “No-CPU” chaotic robots: from classroom to commerce. IEEE Circ Syst Mag, 10(1): 46-53.

[27]Torres M, Pelta DA, Verdegay JL, et al., 2016. Coverage path planning with unmanned aerial vehicles for 3D terrain reconstruction. Expert Syst Appl, 55:441-451.

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

[29]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.

[30]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.

[31]Zheng Z, Liu Y, Zhang XY, 2016. The more obstacle information sharing, the more effective real-time path planning? Knowl-Based Syst, 114:36-46.

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