Path Planning for Mobile Robot Navigation in Unknown Indoor Environments Using Hybrid PSOFS Algorithm

Mohd Nadhir Ab Wahab,Ching May Lee,Muhammad Firdaus Akbar,Fadratul Hafinaz Hassan

doi:10.1109/access.2020.3021605

Mohd Nadhir Ab Wahab, Ching May Lee + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.3021605

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Abstract

Over the past few years, mobile robots are widely used in various industries because they can navigate in dynamic environments and carry out everyday tasks efficiently. Path planning undoubtedly plays an important role in mobile robot navigation, thus becoming one of the most researched topics in the field of robotics. The metaheuristic algorithms have been extensively studied in recent years to solve the path planning problems the same way as the optimization problems were solved, or in other words, plan the optimum path for the robot to navigate from the starting point to the destination. In this research, a mobile robot is launched to find its path from the starting point to the destination in three different simulated environments using a proposed hybrid metaheuristic algorithm between Particle Swarm Optimization and Fringe Search Algorithm, named PSOFS, and its simultaneous localization and mapping (SLAM) capability. During runtime, the path is optimized by considering the path length. The performance of PSOFS for local path planning is compared against two existing algorithms by evaluating the path smoothness as well as robot safety. The results showed that PSOFS has successfully generated shorter, smoother, and safer paths than the algorithms for mobile robot navigation in unknown indoor environments.

Highlights

Over the last few years, robotics and automation have gradually developed in parallel to carry out tasks in almost every area better and eventually replace manual labor, such as autonomous freight transport
Each algorithm is run for 20 times to obtain the optimum path for the robot to navigate in all worlds
This paper is aimed to solve the problem of planning the optimum path for a mobile robot to navigate in unknown indoor environments

Summary

Introduction

Over the last few years, robotics and automation have gradually developed in parallel to carry out tasks in almost every area better and eventually replace manual labor, such as autonomous freight transport. Based on a systematic literature review by [1], autonomous navigation for indoor mobile robots, especially those that function based on vision, did not receive as much attention as autonomous navigation of road vehicles, cars and trucks. Indoor mobile robots such as aerial and ground robots must consider different locomotion mechanisms and unstructured environments. Aerial robots fly in the sky with their wings and ground robots move on the ground with their wheels. These generated more complicated locomotion mechanisms with unpredicted environments that needed more in-depth study.

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