PARTICLE SWARM OPTIMIZATION APPROACH IN ROUTE NAVIGATION FOR PoSVI-Cane

Abstract

Conventional white canes have been used for ages to help those with visual impairment to scan their surroundings as well as detecting potential obstacles. But these canes are not capable of providing any other information, nor helping the blinds to travel independently and efficiently. Hence, numerous research and solutions have been proposed to overcome and improve the function of white canes. These devices are nevertheless expensive, becoming more unaffordable for low-income categories.   Therefore, this paper presents the development of a low-cost navigation device – White Cane with Positioning Solution for Visually Impaired (PoSVI-Cane) that can assist those who are visually impaired to travel confidently, even with unfamiliar routes. In this work, path planning component is embedded to the normal white cane, which further improve its function. Here, Particle Swarm Optimization (PSO) path planning algorithm computes the shortest possible path based on the collection of coordinates along the pedestrian walkway. Results from the experiments shows that employing PSO algorithm in the device manage to assist VIP to travel independently. The cost of path at the optimal route is 823 at 40 iterations. In addition, only low-cost components are used to ensure that the total cost of the proposed cane is low, without jeopardizing its function.