基于模糊控制器的网络机器人实时导航策略

K. K. Pandey, P. K. Mohanty, D. Parhi
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引用次数: 6

摘要

近十年来,复杂系统自主移动机器人的设计涉及到众多异构组件(软件和硬件)之间的相互作用,并根据其应用;它们被大量用于人类参与受限、无法管理或危险的环境中。机器人在工作环境下的合理运动是研究人员面临的一个具有挑战性的课题;因此,移动机器人导航系统的研究日益深入。因此,我们设计了移动机器人控制器算法,帮助移动机器人根据给定的任务在环境中导航并避开障碍物。为了有效地避开障碍物,通过复杂的路径(即被各种类型的障碍物包围)到达目标位置,我们设计了基于传感器集成的模糊逻辑控制器,根据障碍物位置变换移动机器人的方向,形成无碰撞路径。在算法中执行一定的输入参数、输出参数、模糊隶属函数和“If-Then规则”模糊接口系统来创建无碰撞路径。所有这些信息被组合在一起以绘制环境图。为了实现无碰撞路径,借助传感器网络,通过点对点改变转向角度来实现避障。控制器覆盖已知起点、目标点和障碍物位置的环境。机器人在目标寻找过程中优先考虑障碍物的规避。通过一系列的仿真验证了所推荐技术的有效性。为了验证所提出控制器的仿真结果,使用了基于3D物理的仿真软件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real time navigation strategies for webots using fuzzy controller
Since last decade, designing of an autonomous mobile robot for complex systems involves the interaction between numerous heterogeneous components (software and hardware) and according to its application; they are heavily used in environments where human involvement is restricted, unmanageable, or hazardous. For researchers, the proper movement of robot inside working environment is the challenging tasks; accordingly, day by day research has been made on navigation system of mobile robot. As a result, we design mobile robot controller algorithms that helps mobile robot to navigate in environment according to given task and avoid obstacle. In order to avoid obstacles in efficient manner and to reach the goal position through complicated path (i.e. surrounded by various types of obstacles), we designed sensor integration based fuzzy logic controller that transform the direction of mobile robot according to obstacle position and create collision free path. To create a collision free path certain input parameter, output parameter, fuzzy membership functions and `If-Then rule' fuzzy interface system are executed in algorithm. All these information are combined together to map the environment. To attain the collision free path, obstacle avoidance is done through changing the steering angle at point to point with the help of sensor network. The controller covers the environment at which starting point, goal point and obstacle position is known. Priority is made to avoid the obstacle during goal seeking behavior by the robot. The efficiency of the recommended technique is confirmed by a succession of simulations. To check the simulation result for proposed controller, 3D Physics-based simulation software is used.
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