Vehicle Motion Planning for the Visually Challenged People Using Ant Colony Optimization | Zendy

S. Prasanna | Zendy; T. S. Indumathi | Zendy

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Vehicle Motion Planning for the Visually Challenged People Using Ant Colony Optimization

Author(s) -

S. Prasanna,

T. S. Indumathi

Publication year - 2021

Publication title -

ymer digital

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.103

H-Index - 5

ISSN - 0044-0477

DOI - 10.37896/ymer20.12/55

Subject(s) - obstacle , computer science , shortest path problem , motion planning , ant colony optimization algorithms , heuristic , obstacle avoidance , constraint (computer aided design) , path (computing) , point (geometry) , start point , real time computing , artificial intelligence , computer vision , engineering , end point , mobile robot , mathematics , robot , geography , graph , computer network , mechanical engineering , geometry , archaeology , theoretical computer science

This paper presents a novel proposal to solve the problem of obstacle detection and path planning for visually challenged people based on simple Ant Colony Optimization Meta-heuristic (SACO-MH). The mission of the path planning problem is to enable the vehicle to move from the starting point to the target point while satisfying certain constraints. Constraint conditions are: not a collision with known or unknown obstacles, away from the obstacle as far as possible, determines the shortest path, shortest time and so on. Obstacle detection is made with the help of sensor technology and it is intimated to the user with the help of a smart watch. A voice based navigation system guides the user

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