Fuzzy Analytic Hierarchy Process-Based Mobile Robot Path Planning

Abstract

This study presents a new path planning method based on Fuzzy Analytic Hierarchy Process (FAHP) for a mobile robot to be effectively operated through a multi-objective decision making problem. Unlike typical AHP, the proposed FAHP has a difference in using triangulation fuzzy number based extent analysis to derive weight vectors among the considerations. FAHP framework for finding the optimal position in this study is defined with the highest level (goal), middle level (objectives), and the lowest level (alternatives). It analytically selects an optimal position as a sub-goal among points on the sensing boundary of the mobile robot considering the three objectives: the travel distance to the target, robot’s rotation, and safety against collision between obstacles. Alternative solutions are evaluated by quantifying the relative importance for the objectives. Comparative results obtained from the artificial potential field, AHP, and FAHP simulations show that FAHP is much preferable for mobile robot’s path planning than typical AHP.

Development of a Hybrid Path Planning Algorithm and a Bio-Inspired Control for an Omni-Wheel Mobile Robot

“…In order to maximize the utilization of the mobile robot, it is essential to generate a path for the dynamic environment. FAHP has the ability to respond to dynamic aspects, such as unknown obstacles and moving targets, as shown in [36,38]. FAHP originated form analytic hierarchy process (AHP), which is one of the most famous multi-purpose decision-making tools and is used in various fields.…”

“…Then, Chang [41] proposed the extent analysis method, thereby replacing Saaty's nine-point pairwise scale to triangular fuzzy numbers. References [36,38] applied FAHP on mobile robot path planning considering multi-objectives such as the travel distance to the target, collision safety with obstacles, and the rotation of the robot to face the target. However, due to the nature of the algorithm, FAHP, which is an online path planning algorithm, cannot guarantee optimal path generation.…”

“…In this section, a hybrid path planning algorithm is proposed. Recently, reference [36,38] developed an FAHP-based path planning algorithm while applying a single robot and multi-robot navigation scenarios, respectively. From these studies, FAHP considered multi-objectives such as distance to the target, safety, and rotation to the target simultaneously.…”

“…Additionally, the A* algorithm is a well-known algorithm. Therefore, in this paper, two algorithms are briefly introduced, and more detailed descriptions of FAHP and A * are replaced by a reference [36,38,48].…”

“…By means of FAHP, the best candidate was selected as the solution for the robot to move. The implementation of the FAHP follows the procedure below (the following were reduced from [38]).…”