Autonomous Mobile Robots

Optimal path planning applied to ant foraging

This work was carried out by Anand Veeraswamy. This work has been published in the paper entitled "Optimal Path Planning Applied to Ant Foraging". It takes a hybridised approach by combining a biologically evolved technique such as Ant Foraging with a mathematically evolved search technique called the A* algorithm.

This is not an attempt to reproduce the exact behaviour of ant colonies. We are more interesting in improving biologically evolved techniques to create more efficient robots.

In this experiment there are 2 kinds of breeds. One is simply the 'Ant' breed and the other is the 'Path-Finding-Ant' breed. The Ants go about their foraging with the help of two pheromone types, i.e. food pheromones and nest pheromones to create trails of food and nest respectively. The Path-Finding-Ant goes about its task which is to use the A* algorithm to find an optimal path between nest and food. Once it has been found the path, it continuously traverses between the food and the nest dropping the appropriate pheromones. The Ant breed also drop pheromones. But since the Path-Finding-Ant is more efficient it finds the path more quickly and this helps the other ants to find the path quickly thereby increasing the efficiency of foraging.

A live simulation is available here

Past projects

• Anand Veeraswamy, M.Sc.
• Immad ud din, M.Sc.