Adaptive multi-robot wide-area exploration and mapping

The exploration problem is a central issue in mobile robotics. A complete terrain coverage is not practical if the environment is large with only a few small hotspots. This paper presents an adaptive multi-robot exploration strategy that is novel in performing both wide-area coverage and hotspot sampling using non-myopic path planning. As a result, the environmental phenomena can be accurately mapped. It is based on a dynamic programming formulation, which we call the Multi-robot Adaptive Sampling Problem (MASP). A key feature of MASP is in covering the entire adaptivity spectrum, thus allowing strategies of varying adaptivity to be formed and theoretically analyzed in their performance; a more adaptive strategy improves mapping accuracy. We apply MASP to sampling the Gaussian and logGaussian processes, and analyze if the resulting strategies are adaptive and maximize wide-area coverage and hotspot sampling. Solving MASP is non-trivial as it comprises continuous state components. So, ...

• Type: Conference
• Year: 2008
• Where: ATAL
• Authors: Kian Hsiang Low, John M. Dolan, Pradeep K. Khosla
• Keywords: Adaptive Multi-robot Exploration, ATAL 2008, Intelligent Agents, Multi-robot Adaptive Sampling, Wide-area Coverage