Interplanetary Trajectory Optimisation Using Ant Colony Algorithms
- Paper number
IAC-05-C1.5.07
- Author
Dr. Gianmarco Radice, University of Glasgow, United Kingdom
- Coauthor
Mr. German Olmo, University of Glasgow, United Kingdom
- Year
2005
- Abstract
The purpose of this paper is to present the results of the application of ant colony algorithms to space mission analysis and design problems, in particular interplanetary trajectory optimisation. Ant colony algorithms are inspired by the behaviour of natural ant colonies, in the sense that they solve their problems by multi agent cooperation using indirect communication through modifications in the environment. Biological ants release a certain amount of pheromone while walking, and each ant prefers to follow a direction that is rich of pheromone. This simple behaviour explains why ants are able to adjust to changes in the environment, such as new obstacles interrupting the currently shortest path. The main idea is to use repeated and often recurrent simulations of artificial ants to generate new solutions to the problem at hand. The ants use information collected during past simulations to direct their search and this information is available and modified through the environment. This optimisation method will be applied to a number of typical interplanetary manoeuvres such as two body, low thrust and multiple gravity assist transfers. It will be shown that the proposed approach was effectively able to find globally minimal Δv solutions for interplanetary transfers giving the expected characterisation of the problem under study. Moreover it will be shown how the method was able to automatically rediscover known solutions along with new ones of practical interest for future planetary explorations.
- Abstract document
- Manuscript document
IAC-05-C1.5.07.pdf (🔒 authorized access only).
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