Quantitative Analysis of Unmanned Ground Vehicles Trajectories Based on Chaos Theory

doi:10.3901/JME.2016.02.127

Abstract

Abstract: The quantitative evaluation of unmanned ground vehicles is difficult. For this problem a quantitative analysis method based on chaos theory is proposed. The ideal trajectory of unmanned ground vehicles is designed applying the five order polynomial method, and the deviation time series are obtained by calculating the deviation of the actual trajectory and the ideal trajectory. Then the phase space of the deviation time series is reconstructed based on C-C method. The Lyapunov exponent of the deviation time series is calculated which the quantitative presentation of unmanned ground vehicles trajectory is. The quantitative presentation of unmanned ground vehicles trajectory of obstacle avoidance is achieved. The phase space of the deviation time series of obstacle avoidance is reconstructed. The Lyapunov exponent of obstacle avoidance is positive which is characterized the chaos of the unmanned ground vehicle and the speed of convergence to the steady state. Experimental results show that the quantitative analysis method based on chaos theory for unmanned ground vehicles trajectory is feasible and effective.

Key words: chaos, Lyapunov exponent, quantitative analysis, unmanned ground vehicles

CLC Number:

TP242

SUN Yang, XIONG Guangming, CHEN Huiyan, JIANG Yan, GONG Jianwei. Quantitative Analysis of Unmanned Ground Vehicles Trajectories Based on Chaos Theory[J]. Journal of Mechanical Engineering, 2016, 52(2): 127-133.

References

[1] WEI Junqing，DOLAN J M，LITKOUHI B. A prediction- and cost function-based algorithm for robust autonomous freeway driving[C/CD]//Intelligent Vehicles Symposium (IV)，2010 IEEE，2010.
[2] SUN Yang，XIONG Guangming，CHEN Huiyan，et al. A cost function-oriented quantitative evaluation method for unmanned ground vehicles[C/CD]//AMT 2011，China，2011：701-706.
[3] SUN Yang，TAO Gang，XIONG Guangming，et al. The fuzzy-AHP evaluation method for unmanned ground vehicles[J]. Applied Mathematics & Information Sciences，2013，7(2)：653-658.
[4] ULRICH N，KEITH W. The behaviour of a mobile robot is chaotic[J]. AISB Journal，2003，1(4)：1-16.
[5] ULRICH N，KEITH W. Quantitative description of robot-environment interaction using chaos theory[J]. Robotics and Autonomous Systems，2005，53：177-193.
[6] 乌尔里希•内姆佐夫，张文增. 移动机器人学科学方法-智能体行为的量化分析[M]. 北京：机械工业出版社，2010. ULRICH N，ZHANG Wenzeng. Scientific methods in mobile robotics：Quantitative analysis of agent behaviour[M]. Beijing：China Machine Press，2010.
[7] SCHÖNER G，DOSE M. A dynamical systems approach to task-level system integration used to plan and control autonomous vehicle motion[J]. Journal of Robotics and Autonomous Systems，1992，10(92)：253-267.
[8] SCHÖNER G，DOSE M，ENGELS C. Dynamics of behavior：Theory and applications for autonomous robot architectures[J]. Journal of Robotics and Autonomous Systems，1995，16(95)：213-245.
[9] ULRICH N. Quantitative analysis of robot –environment interaction—towards “scientific mobile robotics”[J]. Robotics and Autonomous Systems，2003，44(1)：55-68.
[10] TOM D，ULRICH N. Quantitative analysis of mobile robot localisation systems[C]//British Conference on Autonomous Mobile Robotics and “Scientific Methods in Mobile Robotics”，Manchester，1997：1361-1371.
[11] 李立，张登材. 空间刚性冗余度机器人混沌运动控制的延迟反馈控制法[J]. 机械工程学报，2005，41(9)：122-127. LI Li，ZHANG Dengcai. Delayed feedback control method for chaotic control of spatial rigid redundant robot[J]. Chinese Journal of Mechanical Engineering，2005，41(9)：122-127.
[12] 石鸿雁，孙昌志. 一种基于混沌优化算法的机器人路径规划方法[J]. 机器人，2005，27(2)：152-157. SHI Hongyan，SUN Changzhi. Path planning method for robot based on chaotic optimization algorithm[J]. Robot，2005，41(9)：122-127.
[13] KEWLANI G，IAGNEMMA K. A multi-element generalized polynomial chaos approach to analysis of mobile robot dynamics under uncertainty[C]//2009 IEEE-RSJ International Conference on Intelligent Robots and Systems，2009：1177-1182.
[14] GAO Meijuan，XU Jin，TIAN Jingwen，et al. Path planning for mobile robot based on chaos genetic algorithm[C]//ICNC 2008：Fourth International Conference on Natural Computation，2008：409-413.
[15] 姜万录，张淑清，王益群. 混沌运动特征的数值试验分析[J]. 机械工程学报，2000，36(10)：13-17. JIANG Wanlu，ZHANG Shuqing，WANG Yiqun. Numerical experimental analysis for chaotic motion characteristics[J]. Chinese Journal of Mechanical Engineering，2000，36(10)：13-17.
[16] 吕金虎，陆君安，陈士华. 混沌时间序列分析及应用[M]. 武汉：武汉大学出版社，2002. LÜ Jinhu，LU Junan，CHEN Shihua. Analysis and application of chaotic time series[M]. Wuhan：Wuhan University Press，2002.
[17] 李克强，王跃建. 基于ITS的行车安全辅助系统[J]. 江苏大学学报，2005，26(4)：294-297. LI Keqiang，WANG Yuejian. Driving assistant system based on ITS[J]. Journal of Jiangsu University，2005，26(4)：294-297.
[18] 游峰. 智能车辆自动换道与自动超车控制方法的研究[D]. 长春：吉林大学，2005. YOU Feng. Study on autonomous lane changing and autonomous overtaking control method of intelligent vehicle[D]. Changchun：Jilin University，2005.