

FOLLOWUS
1.School of Computer Science and Technology, Shandong University of Technology, Zibo 255000, China
2.School of Mechanical, Electrical & Information Engineering, Shandong University (Weihai), Weihai 264209, China
‡Corresponding author
Received:15 May 2022,
Revised:2022-07-22,
Published:0 February 2023
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Caihong LI, Cong LIU, Yong SONG, et al. 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.
Caihong LI, Cong LIU, Yong SONG, et al. 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. DOI: 10.1631/FITEE.2200211.
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。
We propose a novel parameter value selection strategy for the Lü 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 Lü 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.
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