Intelligence without representation
Artificial Intelligence
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Future Generation Computer Systems
A new kind of science
Self-Organization in Biological Systems
Self-Organization in Biological Systems
Ant colony optimization theory: a survey
Theoretical Computer Science
ACOhg: dealing with huge graphs
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Obstacle Avoidance Path Planning for Mobile Robot Based on Ant-Q Reinforcement Learning Algorithm
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Review: A review of ant algorithms
Expert Systems with Applications: An International Journal
Off-line vs. on-line tuning: a study on MAX–MIN ant system for the TSP
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Ant colony extended: search in solution spaces with a countably infinite number of solutions
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
This paper introduces the use of a swarm algorithm, derived from Ant Colony Optimisation, to solve path planning problems for autonomous vehicles. The purpose is to obtain optimal trajectories for manoeuvres of Autonomous Surface Vessels. The algorithm works with a model of the vehicle, and the solutions achieved are always feasible. With enough time, it can also obtain trajectories very close to the optimal. Provided the appropriate modifications the algorithm can be applied to solve other combinatorial optimisations problems with a non restricted number of feasible solutions. The methodology is tested through simulations on open sea manoeuvres and scenarios with the presence of obstacles.