Modified robust panel method for mobile robot path planning in partially unknown static and dynamic environments

This paper proposes a novel panel method, called modified robust panel method (MRPM), useful to represent open polygonal chains. MRPM extends an existing panel method approach in order to account for moving obstacles. It is effective for the mobile robot path planning in both static and dynamic environments under partially unknown conditions satisfying real-time requirements. The robustness of the method lays in automatically adjusting the potential field parameters based on the obstacle shapes and sizes taking in account all field segments. These parameters need to be limited so that convergence to the goal position is guaranteed. An activation window and an algorithm to select the relevant obstacles are also presented in order to reduce the computation time. The modified Histogramic-In-Motion-Map (HIMM) algorithm is used to continuously update a grid-based map in which each cell stores the probability of the related region that is occupied by an obstacle. In order to verify the proposed methods a three-layered robot navigation system is developed. The effectiveness and robustness of the proposed methods are demonstrated through simulations.

I. Introduction

Recently, there has been an increasing interest in developing computationally efficient motion planning and control algorithms which allow the robot to move safely through unknown environments [1]. Particular attention is paid to autonomous robots which can accomplish assignments without human interaction. In order to execute necessary tasks, robots should produce an optimal and feasible path avoiding obstacles based on some predefined criterion, such as the energy consumption, safety, time execution, etc. [2], [3].