The development of techniques for autonomous navigation in real-world environments constitutes one of the major trends in the current research on robotics. An important problem in autonomous navigation is the need to cope with the large amount of uncertainty that is inherent of natural environments. Fuzzy logic has features that make it an adequate tool to address this problem. In this paper, we review some of the possible uses of fuzzy logic in the field of autonomous navigation. We focus on four issues: how to design robust behavior-producing modules; how to coordinate the activity of several such modules; how to use data from the sensors; and how to integrate high-level reasoning and low-level execution. For each issue, we review some of the proposals in the literature, and discuss the pros and cons of fuzzy logic solutions.

The uses of fuzzy logic in autonomous robot navigation

This study of robot motion planning in dynamic domains presents algorithms for generating motion in an environment that changes over time. Their computational costs are also analyzed. The ability to plan motion in a dynamic domain is of critical importance to an autonomous robotic system that must operate in the presence of moving obstacles or other robots. The most important feature of the book is the presentation of algorithmic solutions to geometric aspects of dynamic motion planning problems which are of fundamental importance in robotics. Topics discussed include planning in time-dependent environments, generation of time-minimal paths in three dimensions, and the co-ordination of multiple mobile agents. The book can serve as a reference for those working on spatial reasoning and autonomous robotic systems.

Motion Planning in Dynamic Environments

A genetic-fuzzy approach for mobile robot navigation among moving obstacles

Most conventional motion planning algorithms that are based on the model of the environment cannot perform well when dealing with the navigation problem for real-world mobile robots where the environment is unknown and can change dynamically. In this paper, a layered goal-oriented motion planning strategy using fuzzy logic is developed for a mobile robot navigating in an unknown environment. The information about the global goal and the long-range sensory data are used by the first layer of the planner to produce an intermediate goal, referred to as the way-point, that gives a favorable direction in terms of seeking the goal within the detected area. The second layer of the planner takes this way-point as a subgoal and, using short-range sensory data, guides the robot to reach the subgoal while avoiding collisions. The resulting path, connecting an initial point to a goal position, is similar to the path produced by the visibility graph motion planning method, but in this approach there is no assumption about the environment. Due to its simplicity and capability for real-time implementation, fuzzy logic has been used for the proposed motion planning strategy. The resulting navigation system is implemented on a real mobile robot, Koala, and tested in various environments. Experimental results are presented which demonstrate the effectiveness of the proposed fuzzy navigation system.

A layered goal-oriented fuzzy motion planning strategy for mobile robot navigation

A fuzzy approach to collision avoidance for automated guided vehicle (AGV) navigation is proposed. Static obstacles with no a priori position information as well as moving obstacles with unknown trajectories are considered in this study. Intuitive and subjective human ideas of collision avoidance are modeled into fuzzy rules. Fuzzy logic is applied in the inference procedure for AGV navigation, such that the AGV is guided from the starting point toward the target without colliding with obstacles. Furthermore, the proposed method can also be used for the navigation of multiple AGVs, where each AGV must avoid other AGVs as well as obstacles in the environment. Simulation results are presented to show the feasibility of the proposed fuzzy approach. © 1994 John Wiley & Sons, Inc.

https://ir.nctu.edu.tw:443/bitstream/11536/2201/1/A1994QM20700006.pdf

Nobuyoshi Enomoto

Papers

Fuzzy control of a mobile robot for obstacle avoidance