Diffusion-based path planning in mobile actuator-sensor networks (MAS-net): some preliminary results

Abstract

In this paper we present preliminary results related to path-planning problems when it is known that the quantities of interest in the system are generated via a diffusion process. The use of mobile sensor-actuator networks (MAS-Net) is proposed for such problems. A discussion of such networks is given, followed by a description of the general framework of the problem. Our strategy assumes that a network of mobile sensors can be commanded to collect samples of the distribution of interest. These samples are then used as constraints for a predictive model of the process. The predicted distribution from the model is then used to determine new sampling locations. A 2-D testbed for studying these ideas is described. The testbed includes a network of ten robots operating as a network using Intel Motes. We also present simulation results from our initial partial differential equation model of the diffusion process in the testbed.