Open AccessVehicle Motion Planning for the Visually Challenged People Using Ant Colony Optimization
Author(s) -
S. Prasanna,
AUTHOR_ID,
T. S. Indumathi,
AUTHOR_ID
Publication year - 2021
Publication title -
ymer
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 , shortest path problem , computer science , ant colony optimization algorithms , motion planning , heuristic , obstacle avoidance , path (computing) , constraint (computer aided design) , point (geometry) , start point , artificial intelligence , real time computing , computer vision , engineering , mobile robot , mathematics , end point , geography , robot , graph , computer network , theoretical computer science , mechanical engineering , geometry , archaeology
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