Theoretical & mathematical concepts formulation behind the development of AI-ML algorithms for path planning in robots

    DOI: https://doie.org/10.0824/Jbse.2024438551

    Sachin R Jadhave , Mayura Shelke , Dr. Jagdisha N , Dr Prashanta G. R


    Keywords:

    AI, ML, DL, Robot, Obstacle, Avoidance, Path, Plan, Goal, Source, Destination, Collision.


    Abstract:

    In this research paper, which is the 1st part of the research article, a brief insight into the theoretical & mathematical modelling concepts of the various types of algorithm development are presented in a concised manner to achieve the desired task, i.e., design of the robot path to move to the destination from the source to the goal in spite of obstacles. Various theoretical concepts of AI & ML algorithms such as the Reinforcement learning, Q-Learning, Deep Learning, Supervised Learning, Un-supervised learning, etc. are being proposed, which are discussed one after the other in a nutshell, first the theoretical concepts are being presented, this is followed by the algorithm development, then the simulated results. The work is divided into a number of sections in the forth coming research papers, where the theoretical concepts of AI & ML presented here are used to develop the hybrid algorithms for the path planning of the robot from the source to the destination. The article is developed in 2 phases, part I & II. The part-I is presented in this research paper, whereas Part II of this research paper is extended to as another research article. The paper concludes with the overall conclusions of the work done in this research article.


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