Abstract

Mobile robots are faced with problems (for ex. path planning) with many alternative solutions (ex. paths) based on several factors, and they must make a selection by quantifying the factors and mathematically evaluating the alternative solutions. Robot path planning is an integral process of mobile robots. A shortest path is generally chosen, however, it is not necessarily the optimal path. Apart from the distance between the start and goal locations, a robot must consider several other factors like the bumpiness, steepness, and crowd on the path. Robots are equipped with sensors like cameras, inertial sensors, and distance sensors to measure these factors. Different paths could be generated between the same start and goal locations considering these factors. The robot must select the optimal path from many paths. The factors which influence the generation of such paths can be dynamic. In this paper we propose to use Fuzzy Analytical Hierarchical Process (Fuzzy-AHP) to analytically select the optimal path from different paths. Fuzzy-AHP provides two navigational approaches, namely, defensive and offensive approaches which can be taken by mobile robots for navigation. In this paper, we present a case study of robot path selection with Fuzzy-AHP.

Highlights

  • A mobile robot continuously makes decisions: for ex. to stop or turn to avoid collision, to increase or decrease speed, or to make way for other people

  • For navigation to service locations, it needs to plan a path from its current location to the goal location

  • Rapidly-exploring random tree, Dijkstra, and other planners have successfully been used for path planning [1]

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Summary

Introduction

A mobile robot continuously makes decisions: for ex. to stop or turn to avoid collision, to increase or decrease speed, or to make way for other people. Rapidly-exploring random tree, Dijkstra, and other planners have successfully been used for path planning [1] Most of these planners generate a shortest path from the start location to the goal location. Apart from the distance between the start and goal locations, a robot must consider several other factors like the bumpiness (i.e., terrain roughness), steepness, and crowd [2] on the path. Process (Fuzzy-AHP) can be used in such situations to make the optimal selection of the path considering multiple factors. We demonstrate the process step-by-step by taking a case study of path selection

Brief Explanation of AHP
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