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INTEGRATED FUZZY GLOBAL PATH FOLLOWING AND OBSTACLE AVOIDANCE FOR MOBILE ROBOTS

机译:移动机器人的综合模糊全局路径跟踪和障碍规避

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摘要

Motion planning is the process of computing a path, i.e., a sequence of robot configurations, al-ing it tp move from one place to another. It is a central problem in the development of autonomous mobile robots. This is true indeed, but when the environment of the robot becomes complex, i.e., uncertain, partially known, with moving obstacles or other robots, it takes much more than global motion planning to achieve motion autonomy. In this case, the ability to detect unexpected events and react accordingly becomes essential. Reactivity provides the robot with an important mechanism to immediate respond to unpredicted environmental changes. This paper describes an intelligent path planning system for omnidirectional mobile robots. Our proposed solution to the dual need for global path planning and reactivity is to adopt a two-level model: at the upper level, a planner provides the system with a global path, based on the available knowledge; at the lower level, a reactive controller follows this given global path, while dealing with the environmental contingencies. The control architecture, presented in this paper, relies upon two main complementary modules: a global path planner, that computes a nominal path between the current configuration of the robot and its goal, and a reactive local planner, whose purpose is to generate the appropriate commands for the actuators of the robot, so as to follow the global path as close as possible, while reacting in real-time to unexpected events by locally adapting the robots movements, so as to avoid collisions with unpredicted or moving obstacles. This reactive local planner consists of two separate fuzzy controllers for path following and obstacle avoidance. The functioning of the proposed system wkh respect to omnidirectional mobile robots and results of simulated experiments will be presented.
机译:运动计划是计算路径(即一系列机器人配置)的过程,并使其从一个地方移动到另一个地方。在自主移动机器人的发展中,这是一个中心问题。确实的确如此,但是当机器人的环境变得复杂,即不确定的,部分已知的,具有移动障碍物或其他机器人的机器人时,要实现运动自主性,所需的工作要比全局运动计划多得多。在这种情况下,检测意外事件并做出相应反应的能力变得至关重要。反应性为机器人提供了一种重要机制,可以立即对意外的环境变化做出响应。本文介绍了一种用于全向移动机器人的智能路径规划系统。我们针对全局路径规划和反应性双重需求的拟议解决方案是采用两级模型:在上层,规划人员根据现有知识为系统提供全局路径;在较低级别,反应性控制器遵循此给定的全局路径,同时处理环境突发事件。本文中介绍的控制体系结构依赖于两个主要的补充模块:全局路径规划器,用于计算机器人当前配置与其目标之间的标称路径;以及反应性局部规划器,其目的是生成适当的路径。命令用于机器人的执行器,以便尽可能接近全局路径,同时通过局部适应机器人的运动对意外事件做出实时反应,从而避免与意外或移动障碍物发生碰撞。该反应式局部计划器由两个独立的模糊控制器组成,用于路径跟随和避障。将介绍拟议系统相对于全向移动机器人的功能以及模拟实验的结果。

著录项

  • 来源
    《Systems Science》 |2001年第4期|p.85-96|共12页
  • 作者单位

    Intelligent Robotics and Automation Laboratory, Signals, Control and Robotics Division, Department of Electrical and Computer Engineering, National Technical University of Athens, Zografou 15773, Athens, Greece;

  • 收录信息 美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 一般工业技术;
  • 关键词

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