Adaptive Sampling of Latent Phenomena using Heterogeneous Robot Teams (ASLaP-HR)

Understand

In this paper, we present an online adaptive planning strategy for a team of robots with heterogeneous sensors to sample from a latent spatial field using a learned model for decision making.

• Current robotic sampling methods seek to gather information about an observable spatial field.
• However, many applications, such as environmental monitoring and precision agriculture, involve phenomena that are not directly observable or are costly to measure, called latent phenomena.
• In our approach, we seek to reason about the latent phenomenon in real-time by effectively sampling the observable spatial fields using a team of robots with heterogeneous sensors, where each robot has a distinct sensor to measure a different observable field.