• Feb 26, 2018 News!'Writing Tips' shared by Prof. Ian McAndrew!   [Click]
  • Mar 06, 2018 News!IJMMM Vol.6, No.4 has been published with online version. 15 peer reviewed articles are published in this issue.   [Click]
  • Dec 29, 2017 News!The submission for 2018 2nd European Conference on Materials, Mechatronics and Manufacturing was over on December 25, 2017.
General Information
    • ISSN: 1793-8198
    • Frequency: Quarterly
    • DOI: 10.18178/IJMMM
    • Editor-in-Chief: Prof. K. M. Gupta, Prof. Ian McAndrew
    • Executive Editor: Ms. Cherry L. Chen
    • Abstracting/Indexing: EI (INSPEC, IET), Chemical Abstracts Services (CAS),  ProQuest, Crossref, Ulrich's Periodicals Directory,  etc.
    • E-mail ijmmm@ejournal.net
Prof. Ian McAndrew
Embry Riddle Aeronautical University, UK.
It is my honor to be the editor-in-chief of IJMMM. I will do my best to help develop this journal better.

IJMMM 2016 Vol.4(2): 127-130 ISSN: 1793-8198
DOI: 10.7763/IJMMM.2016.V4.239

Ant-Air Self-learning Algorithm for Path Planning in a Cluttered Environment

Rafiq Ahmad and Peter Plapper
Abstract—Path planning in unstructured area while dealing with narrow spaces is an area of research which is receiving extensive interest. Many existing algorithms are able to produce safe paths but the presented concepts are either not adapted to narrow spaces or they are unable to learn from the past experience to improve repeated movements from the same agent or followed trajectories by other agents. This paper introduces an original concept based on Ant-Air phenomenon for safe path planning in a cluttered environment where narrow passages are treated. The algorithm presented is able to learn from the past experience and hence improve the already generated trajectory further by using some lessons learned from the past experience. The concept is applicable in various domains such as mobile robot path planning, manipulator trajectory generation and part movement in narrow passages in real or virtual assembly/disassembly process.

Index Terms—Path planning, collision detection and avoidance, self-learning algorithm, assembling or disassembling, narrow spaces.

The authors are with University of Luxembourg, L-1359 Luxembourg, Pakistan (e-mail: rafiq.ahmad@uni.lu, peter.plapper@uni.lu).


Cite: Rafiq Ahmad and Peter Plapper, "Ant-Air Self-learning Algorithm for Path Planning in a Cluttered Environment," International Journal of Materials, Mechanics and Manufacturing vol. 4, no. 2, pp. 127-130, 2016.

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