Novel Algorithm for Mobile Robot Path Planning in Constrained Environment

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 2698 CMC, 2022, vol.71, no.2 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.

Stability Analysis and Navigational Techniques of Wheeled Mobile Robot: A Review

“…The foundational exploration of wheeled mobile robots (WMRs) to assess the mechanical system's dynamics involves a kinematic inquiry, which is imperative for ensuring the seamless execution of predefined trajectories [12]. This analytical process yields insights into devising control software for the WMR hardware, as well as for the design of robots tailored to tasks demanding a comprehensive grasp of the mechanical conduct of the robot [13]. Given that WMRs necessitate lower exertion compared to legged or tracked robots, they hold significant potential for widespread adoption within contemporary industrial scenarios [14,15].…”

A Generalized Laser Simulator Algorithm for Mobile Robot Path Planning with Obstacle Avoidance

“…Furthermore, the algorithm presented an optimized version that will generate pathways with lesser nodes and a greater success rate while being computationally efficient. It is an enhancement of the laser simulator method, which has been successfully adopted in many works [ 62 , 63 , 64 , 65 ] and an extension of [ 1 ] for avoiding obstacles during path planning.…”

“…This section explains how to determine a feasible collision-free path using the proposed generalized laser simulator algorithm. This algorithm is an enhancement of the laser simulator method, which has been successfully adopted in many works [ 60 , 61 , 62 , 63 ] and an extension of [ 1 ] for avoiding obstacles during path planning.…”

“…In [ 1 ], the GLS algorithm has been utilized to determine the path within the restricted environment. It finds the borders of environments and determines the next position of robot through generation of a series of points like waves from the beginning until the goals positions.…”

“…One of the most significant processes in the autonomous navigation is path planning [ 1 ]. Path planning involves the determination of a possible path for a mobile robot to move from a start to a target location in a particular environment while considering optimization parameters like path distance, time and path smoothness [ 2 , 3 , 4 ].…”