Search methodologies for efficient planetary site selection

Landing on distant planets is always a challenging task due to the distance and hostile environments found. In the design of autonomous hazard avoidance systems we find the particularly relevant task of landing site selection, that has to operate in real-time as the lander approaches the planet's surface. Seeking to improve the computational complexity of previous approaches to this problem, we propose the use of non-exhaustive search methodologies. A comparative study of several algorithms, such as Tabu Search and Particle Swarm Optimization, was performed. The results are very promising, with Particle Swarm Optimization showing the capacity to consistently produce solutions of very high quality, on distinct landing scenarios.

• Type: Conference
• Year: 2009
• Where: CEC
• Authors: Luís F. Simões, Tiago C. Pais, Rita Almeida Ribeiro, Gregory Jonniaux, Stephane Reynaud
• Keywords: Artificial Intelligence, Autonomous Hazard Avoidance, CEC 2009, Landing Site Selection, Particle Swarm Optimization