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Path planning of humanoids based on artificial potential field method in unknown environments

机译:未知环境中基于人工势场法的类人动物路径规划

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摘要

In this paper, an artificial potential field based navigational controller has been developed for motion planning of humanoid robots. Here, NAO robots are used as the humanoid platform using the underlying principles of potential field based method. The movement of the robot is considered to be under a negative gradient scheme by the combined effect of attractive and repulsive forces generated due to target and obstacles, respectively. The working of the controller is tested in a V-REP simulation platform, and the simulation results are validated through a real-time experimental set-up developed under laboratory conditions. Here, the navigation of both single and multiple humanoids has been attempted. For avoiding intercollision among multiple humanoids during their navigation in a common platform, a Petri-Net control scheme has been proposed. The results obtained from both the simulation and experimental platforms are compared against each other with a good agreement between them having minimal percentage of deviations. Finally, the proposed controller is also evaluated against another existing navigational model, and a significant performance improvement has been observed.
机译:在本文中,已经开发了一种基于人工势场的导航控制器,用于拟人机器人的运动规划。在这里,NAO机器人根据潜在场域方法的基本原理被用作人形机器人平台。通过分别由于目标和障碍物产生的吸引力和排斥力的综合作用,可以认为机器人的运动处于负梯度方案下。在V-REP仿真平台上测试控制器的工作情况,并通过在实验室条件下开发的实时实验设置验证仿真结果。在这里,已经尝试了单个和多个类人动物的导航。为了避免多个类人动物在公共平台上的导航过程中相互碰撞,提出了一种Petri-Net控制方案。从仿真平台和实验平台获得的结果相互比较,并且两者之间具有很好的一致性,且偏差百分比极小。最后,还针对另一个现有的导航模型对提出的控制器进行了评估,并且观察到了显着的性能改进。

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