• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International Journal of Artificial Intelligence Tools: Architectures, Languages, Algorithms >An Intelligent Path Planning Approach for Humanoid Robots Using Adaptive Particle Swarm Optimization
【24h】

An Intelligent Path Planning Approach for Humanoid Robots Using Adaptive Particle Swarm Optimization

机译：自适应粒子群优化的人形机器人智能路径规划方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The current investigation is focused on the development of a novel navigational controller for the optimized path planning and navigation of humanoid robots. The proposed navigational controller works on the principle of adaptive particle swarm optimization. To improve the working pattern of a simple particle swarm optimization controller, some modifications are done to the controlling parameters of the algorithm. The input parameters to the controller are the sensory information in forms of obstacle distances, and the output from the controller is the required turning angle to safely reach the target position by avoiding the obstacles present in the path. By applying the logic of the adaptive particle swarm optimization, humanoid robots are tested in simulation environments. To validate the results, an experimental platform is also developed under laboratory conditions, and a comparison has been performed between the simulation and experimental results. To test the proposed controller in both static and dynamic environments, it is implemented in the navigation of single as well as multiple humanoid robots. Finally, to ensure the efficacy of the proposed controller, it is compared with some of the existing techniques available for navigational purpose.
机译：目前的调查专注于开发新型航行控制员，以获得人形机器人的优化路径规划和导航。建议的导航控制器适用于自适应粒子群优化原理。为了提高简单粒子群优化控制器的工作模式，对算法的控制参数进行了一些修改。控制器的输入参数是障碍物距离形式的感觉信息，并且通过避免路径中存在的障碍物，控制器的输出是所需的转向角度，以安全地到达目标位置。通过应用自适应粒子群优化的逻辑，在仿真环境中进行了人形机器人。为了验证结果，还在实验室条件下开发了实验平台，在模拟和实验结果之间进行了比较。为了在静态和动态环境中测试所提出的控制器，它在单个和多个人形机器人的导航中实现。最后，为了确保所提出的控制器的功效，与可用于导航目的的一些现有技术进行比较。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号