基于混合模糊遗传算法的仿人机器人导航路径优化

IF 1.3 Q4 ROBOTICS
Asita Kumar Rath, D. Parhi, H. Das, P. Kumar, M. Muni, Kitty Salony
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引用次数: 24

摘要

目的类人因其在关键干预中取代人类努力的能力,已成为许多从事机器人研究的研究人员的吸引力中心。因此,导航和路径规划已成为人形模型最有前途的研究领域之一。本文提出了一种将模糊逻辑控制器与遗传算法相结合的仿人机器人路径规划方法,以避免杂乱环境中的障碍物并成功到达目标位置。本文旨在讨论这些问题。设计/方法/方法这里,人形机器人的最近障碍物距离和方位角的传感器输出首先作为模糊逻辑控制器的输入,并且获得第一转角(TA)作为中间输出。在第二步骤中,从模糊逻辑控制器导出的第一TA与其他输入一起再次提供给GA控制器,并且获得第二TA作为最终输出。所开发的混合控制器已在V-REP仿真平台上进行了测试,并在实验装置中验证了仿真结果。发现通过实现所提出的混合控制器,仿人机器人在模拟和实验平台上都成功地避开了舞台上的障碍物,达到了预定的目标位置。将模拟平台和实验平台获得的结果在路径长度和所用时间方面进行了比较,并在误差百分比最小的情况下观察到了密切的一致性。独创性/价值类人因其模仿人类行为的能力而被认为比轮式机器人更高效。目前的研究是开发一种新的混合控制器,该控制器考虑了模糊逻辑和遗传算法,用于仿人机器人的导航分析。所开发的控制方案已在模拟和实时环境中进行了测试,并在从中获得的结果之间找到了适当的一致性。所提出的方法也可以应用于其他人形形式,该技术可以作为人形导航的先驱艺术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Path optimization for navigation of a humanoid robot using hybridized fuzzy-genetic algorithm
Purpose Humanoids have become the center of attraction for many researchers dealing with robotics investigations by their ability to replace human efforts in critical interventions. As a result, navigation and path planning has emerged as one of the most promising area of research for humanoid models. In this paper, a fuzzy logic controller hybridized with genetic algorithm (GA) has been proposed for path planning of a humanoid robot to avoid obstacles present in a cluttered environment and reach the target location successfully. The paper aims to discuss these issues. Design/methodology/approach Here, sensor outputs for nearest obstacle distances and bearing angle of the humanoid are first fed as inputs to the fuzzy logic controller, and first turning angle (TA) is obtained as an intermediate output. In the second step, the first TA derived from the fuzzy logic controller is again supplied to the GA controller along with other inputs and second TA is obtained as the final output. The developed hybrid controller has been tested in a V-REP simulation platform, and the simulation results are verified in an experimental setup. Findings By implementation of the proposed hybrid controller, the humanoid has reached its defined target position successfully by avoiding the obstacles present in the arena both in simulation and experimental platforms. The results obtained from simulation and experimental platforms are compared in terms of path length and time taken with each other, and close agreements have been observed with minimal percentage of errors. Originality/value Humanoids are considered more efficient than their wheeled robotic forms by their ability to mimic human behavior. The current research deals with the development of a novel hybrid controller considering fuzzy logic and GA for navigational analysis of a humanoid robot. The developed control scheme has been tested in both simulation and real-time environments and proper agreements have been found between the results obtained from them. The proposed approach can also be applied to other humanoid forms and the technique can serve as a pioneer art in humanoid navigation.
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来源期刊
CiteScore
3.50
自引率
0.00%
发文量
21
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