Open Access

ARTICLE

Novel Algorithm for Mobile Robot Path Planning in Constrained Environment

Aisha Muhammad^1,5, Mohammed A. H. Ali^2,*, Sherzod Turaev³, Ibrahim Haruna Shanono^4,5, Fadhl Hujainah⁶, Mohd Nashrul Mohd Zubir², Muhammad Khairi Faiz², Erma Rahayu Mohd Faizal¹, Rawad Abdulghafor⁸

1 Faculty of Manufacturing Engineering, Universiti Malaysia Pahang (UMP), Pekan, 26600, Malaysia
2 Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia
3 Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates
4 Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang (UMP), Pekan, 26600, Malaysia
5 Department of Mechatronics Engineering, Faculty of Technology, Bayero University, Kano (BUK), 700241, Nigeria
6 Computer Science and Engineering Department, Chalmers and University of Gothenburg, 41296, Gothenburg, Sweden
7 Department of Artificial Intelligence, Faculty of Computer Science and Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia
8 Department of Computer Science, Faculty of Information and Communication Technology, International Islamic University Malaysia, 53100, Kuala Lumpur, Malaysia

* Corresponding Author: Mohammed A. H. Ali. Email:

Computers, Materials & Continua 2022, 71(2), 2697-2719. https://doi.org/10.32604/cmc.2022.020873

Received 12 June 2021; Accepted 29 September 2021; Issue published 07 December 2021

Abstract

This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobile robot path planning problem in a two-dimensional map with the presence of constraints. This approach gives the possibility to find the path for a wheel mobile robot considering some constraints during the robot movement in both known and unknown environments. The feasible path is determined between the start and goal positions by generating wave of points in all direction towards the goal point with adhering to constraints. In simulation, the proposed method has been tested in several working environments with different degrees of complexity. The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. The results revealed that the proposed method has shortest path length, less computational time and the best smooth path. As an average, GLS is faster than A* and LS by 7.8 and 5.5 times, respectively and presents a path shorter than A* and LS by 1.2 and 1.5 times. In order to verify the performance of the developed method in dealing with constraints, an experimental study was carried out using a Wheeled Mobile Robot (WMR) platform in labs and roads. The experimental work investigates a complete autonomous WMR path planning in the lab and road environments using a live video streaming. Local maps were built using data from a live video streaming with real-time image processing to detect segments of the analogous-road in lab or real-road environments. The study shows that the proposed method is able to generate shortest path and best smooth trajectory from start to goal points in comparison with laser simulator.

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