| Issue |
MATEC Web Conf.
Volume 398, 2024
2nd International Conference on Modern Technologies in Mechanical & Materials Engineering (MTME-2024)
|
|
|---|---|---|
| Article Number | 01011 | |
| Number of page(s) | 9 | |
| DOI | https://doi.org/10.1051/matecconf/202439801011 | |
| Published online | 25 June 2024 | |
Searching Heuristically Optimal Path Using a New Technique of Bug0 Algorithm in Swarm Robotics
1 Department of Mechatronics Engineering, National University of Sciences and Technology (NUST), CEME, 43701 Rawalpindi, Pakistan
2 Department of Mechanical Engineering, National University of Sciences and Technology (NUST), CEME, 43701 Rawalpindi, Pakistan
* Hamza Sohail: hamza.sohail@ceme.nust.edu.pk
Bug Algorithms in robotics field play an important role in path planning. The main challenge in conventional bug algorithms is searching the cluttered environment. To solve this problem a method is introduced which uses the concept of swarm robotics that helps in finding path using coordination between robots in swarm. The challenge in this research article is to find a path which is heuristically optimal. A type of bug algorithm is introduced in which parent bug sends two of its child bugs. Each of them has capability of searching in different directions. After searching the path from both sides, parent bug follows the path which is heuristically optimal. Parent and child bugs are equipped with tactile sensors to follow the perimeter of an obstacle. Illustrative simulation results show two test cases in which different scenarios are presented. Results are compared with of bug0 algorithm that is visualized in configuration space as well as in workspace to find the heuristically optimal path.
Key words: Mobile Robotics / Swarm Robotics / Heuristics / Path Planning / Bug Algorithm / Motion Planning
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.