An overview of MOOS-IvP and a brief users guide to the IvP helm autonomy software
- M. R. Benjamin, J. J. Leonard, H. Schmidt, P. M. Newman
- Technical Report MIT-CSAIL-TR-2009-028,
Water quality monitoring is still mostly done by taking manual water samples and sensor measurements from boats. To enable extensive, efficient and repeatable environmental monitoring, there is a need for ‘ready to sample’ robot systems, which do not require individual vehicle control, or a lot of prior information. This paper describes an approach to decentralized adaptive formation control for environmental sampling. An autonomous surface vehicle (ASV) leads a team of autonomous underwater vehicles (AUVs) to sample a lake environment. The ASV passes a constraint to the AUVs, and the AUVs use this to choose an allowed formation, and solve the assignment problem to determine their position in the formation, in a distributed manner. The approach is tested in simulation and compared to leader-follower formation control. Results show the potential for constraint-induced formation switching in adaptive formation control towards a safe, fully autonomous heterogeneous team of lake sampling robots.