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MOTION CONTROL FOR MOBILE ROBOT OBSTACLE AVOIDANCE AND NAVIGATION: A FUZZY LOGIC-BASED APPROACH

机译:移动机器人避障和导航的运动控制:一种基于逻辑的模糊方法

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One of the ultimate goals of mobile robotics research is to build robots that can safely carry out missions in hazardous and populated environments. Most of today's commercial mobile devices scale poorly along this dimension. Their motion planning relies on accurate, static models of the environments, and therefore they often fail their mission if humans or other unpredictable obstacles block their path. To build autonomous mobile robots one has to build systems that can perceive their environments, react to unforeseen circumstances, and plan dynamically in order to achieve their mission. Thus, the objective of the motion planning and control problem is to find collision-free trajectories, in static or dynamic environments containing some obstacles, between a start and a goal configuration. It has attracted much research in recent years. In this context the term control has a broad meaning that includes many different controls, such as low-level motor control, and behaviour control, where behaviour represents many complicated tasks, like obstacle avoidance and goal seeking. This article describes an intelligent motion planning and navigation system for omnidirectional mobile robots based on fuzzy logic. Owing to its simplicity and hence its short response time, the fuzzy navigator is especially suitable for on-line applications with strong real-time requirements. On-line planning is an on-going activity. The planner receives a continuous flow of information about occurring events and generates new commands in response to the incoming events, while previously planned motions are being executed. The fuzzy-rule-base of the proposed system combines the repelling influence, which is related to the distance and the angle between the robot and nearby obstacles, with the attracting influence produced by the distance and the angular difference between the actual direction and position of the robot and the final configuration, to generate actuating commands for the mobile platform. It can be considered as an on-line local navigation method for omnidirectional mobile robots for the generation of instantaneous collision-free motions. This reactive system is especially suitable for real-time applications. The use of fuzzy logic leads to a transparent system which can be tuned by hand or by a set of learning rules. Furthermore, this approach allows obstacle avoidance and navigation in dynamic environments. The functioning of the fuzzy motion planner with respect to omnidirectional mobile robots and results of simulated experiments are presented.
机译:移动机器人技术研究的最终目标之一是制造可以在危险和人口稠密的环境中安全执行任务的机器人。当今大多数商用移动设备在此方面的扩展性很差。他们的运动计划依赖于准确,静态的环境模型,因此,如果人类或其他不可预测的障碍物阻碍了他们的前进,他们通常会无法完成任务。为了构建自主的移动机器人,必须构建能够感知其环境,对不可预见的情况做出反应并动态规划以实现其任务的系统。因此,运动计划和控制问题的目的是在起始和目标配置之间找到包含某些障碍的静态或动态环境中的无碰撞轨迹。近年来,它吸引了很多研究。在这种情况下,术语“控制”具有广泛的含义,包括许多不同的控制,例如低级电机控制和行为控制,其中行为表示许多复杂的任务,例如避开障碍物和寻求目标。本文介绍了一种基于模糊逻辑的全向移动机器人智能运动计划与导航系统。由于其简单性,因此响应时间短,因此模糊导航器特别适用于对实时性要求很高的在线应用。在线计划是一项持续的活动。在执行先前计划的动作时,计划人员会接收有关发生事件的连续信息流,并响应于传入事件而生成新命令。所提出系统的模糊规则基础将排斥力与机器人与附近障碍物之间的距离和角度有关,并与距离和实际障碍物的实际方向与位置之间的角度差产生了吸引力。机器人和最终配置,以生成用于移动平台的启动命令。它可以被认为是全向移动机器人的在线本地导航方法,用于产生瞬时无碰撞运动。该反应系统特别适合于实时应用。模糊逻辑的使用导致透明的系统,该系统可以手动或通过一组学习规则进行调整。此外,这种方法允许在动态环境中避开障碍物并进行导航。给出了模糊运动计划器相对于全方位移动机器人的功能以及仿真实验的结果。

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