Robot Navigation Model in a Multi-Target Domain Amidst Static and Dynamic Obstacles

Abstract

This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. A hybrid modelling scheme premised on geometrical considerations was applied to determine the length of obstacles encountered by the robot. Also, a dynamic model premised on the collapse of the radiation cone was proposed and used to estimate the velocity of a dynamic obstacle along the robot's path.