Reverse-Twister Swarm Search Algorithm Design: NASA Swarmathon Competition

摘要

To revolutionize space exploration techniques, the DustySWARM team from Texas A&M International University took the challenge to improve current search algorithms. The focus of the research was to create an efficient search algorithm applicable to the future mission of NASA space exploration. The use of autonomous search rovers that can react to their environment facilitates the exploration of unknown territories. Furthermore, swarms of autonomous robots reduce the data and resource collection period. In nature, swarms of animals and insects have developed, by instinct, searching systems to collect resources for food and shelter. Within the groups, the ability to achieve their goal of resource collection is obtained by systems of communication and reactions to the environment. Similarly, robot swarms can collaborate to explore unknown terrain. Previous search algorithms have been developed, such as the iAnt code developed by the University of New Mexico, which implements the use of sensor feedback and programmed decision logic to search for and collect resources.