Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : path planning


A Review on Path Planning Algorithms for Mobile Robots

Mustafa S. Abed; Omar F. Lutfy; Qusay F. Al-Doori

Engineering and Technology Journal, 2021, Volume 39, Issue 5A, Pages 804-820
DOI: 10.30684/etj.v39i5A.1941

Mobile robots use is rising every day. Path planning algorithms are needed to make a traveler of robots with the least cost and without collisions. Many techniques have been developed in path planning for mobile robot worldwide, however, the most commonly used techniques are presented here for further study. This essay aims to review various path planning strategies for mobile robots using different optimization methods taken recent publisher’s paper in last five year.

Path Planning of Mobile Robot Using Improved Artificial Bee Colony Algorithm

Rkaa T. Kamil; Mohamed J. Mohamed; Bashra K. Oleiwi

Engineering and Technology Journal, 2020, Volume 38, Issue 9, Pages 1384-1395
DOI: 10.30684/etj.v38i9A.1100

A modified version of the artificial Bee Colony Algorithm (ABC) was suggested namely Adaptive Dimension Limit- Artificial Bee Colony Algorithm (ADL-ABC). To determine the optimum global path for mobile robot that satisfies the chosen criteria for shortest distance and collision–free with circular shaped static obstacles on robot environment. The cubic polynomial connects the start point to the end point through three via points used, so the generated paths are smooth and achievable by the robot. Two case studies (or scenarios) are presented in this task and comparative research (or study) is adopted between two algorithm’s results in order to evaluate the performance of the suggested algorithm. The results of the simulation showed that modified parameter (dynamic control limit) is avoiding static number of limit which excludes unnecessary Iteration, so it can find solution with minimum number of iterations and less computational time. From tables of result if there is an equal distance along the path such as in case A (14.490, 14.459) unit, there will be a reduction in time approximately to halve at percentage 5%.

Development of Path Planning Algorithm Using Probabilistic Roadmap Based on Ant Colony Optimization

Mohammed I. Abdulakareem; Firas A. Raheem

Engineering and Technology Journal, 2020, Volume 38, Issue 3A, Pages 343-351
DOI: 10.30684/etj.v38i3A.389

In this paper, a unique combination among probabilistic roadmap, ant colony optimization, and third order B-spline curve has been proposed to solve path-planning problem in complex and very complex environments. This proposed method can be divided into three stages. First stage is to construct a random map depending on the environment complexity using probabilistic roadmap algorithm. This could be done by sampling N nodes randomly in complex and very complex static environments, then connecting these nodes together according to some criteria or conditions. The constructed roadmap contains huge number of possible random paths that may connect the start and the goal points together. Second stage includes finding path within the pre-constructed roadmap. Ant colony optimization is selected to find or to search the best path between start and goal points. Finally, the third stage uses B-spline curve to smooth and reduce total length of the found path in the previous stage where path’s length has been reduced by 1% in first environment and by 15% in second environment. The results of the proposed approach ensure feasible path between start and goal points in complex and very complex environment. In addition, the path is guaranteed to be shortest, smooth, continues and safe.