Obstacle Avoidance in a Three-Dimensional Dynamic Environment Based on Fuzzy Dynamic Windows

Ce Xu,Mingyi Xia,Zhenbang Xu

doi:10.3390/app11020504

Abstract

This paper presents a real-time path planning approach for controlling the motion of space-based robots. The algorithm can plan three-dimensional trajectories for agents in a complex environment which includes numerous static and dynamic obstacles, path constraints, and/or performance constraints. This approach is extended based on the dynamic window approach (DWA). As the classic reactive method for obstacle avoidance, DWA uses an optimized function to select the best motion command. The original DWA optimization function consists of three weight terms. Changing the weights of these terms will change the behavior of the algorithm. In this paper, to improve the evaluation ability of the optimization function and the robot’s ability to adapt to the environment, a new optimization function is designed and combined with fuzzy logic to adjust the weights of each parameter of the optimization function. Given that DWA has the defect of local minima, which makes the robot hard to escape U-shaped obstacles, a dual dynamic window method and local goals are adopted in this article to help the robot escape local minima. By comparison, the proposed method is superior to traditional DWA and fuzzy DWA (F_DWA) in terms of computational efficiency, smoothness and security.

Highlights

It is expected that space autonomous robotics will be used to complete complex and dangerous tasks in space as space technology develops [1]
To address the navigation problem in the three-dimensional environment, this paper proposes a fuzzy dynamic window approach (DF_DWA)
We mainly focus on the 3D real-time trajectory planning of the kind of space-based robots, such as SPHERES [38] and astronaut assistant robots [39]

Summary

Introduction

It is expected that space autonomous robotics will be used to complete complex and dangerous tasks in space as space technology develops [1]. As a robot completes a mission, it needs to plan a safe trajectory from a starting point to a target point. Collisions and path optimization are the main issues relating to the planning of the trajectory (i.e., navigation). Some notable global navigation algorithms avoid the collision problem by building a global environment map: e.g., A* [3], D* [4], FD* [5], and RRT [6]. When planning a path on a map, the optimization goal is usually the shortest path or the lowest energy use

Methods

Results

Conclusion