# Mobile robots as remote sensors for spatial point process models

#### *2016 IEEE/RSJ International Conference on Intelligent Robots and Systems*, Oct, 2016.

Paul Reverdy and D. E. Koditschek

Electrical and Systems Engineering, University of Pennsylvania

Full PDF (preprint) | Penn Scholarly Commons

Fig. 1. Example trajectory.

Abstract |

Spatial point process models are a commonly-used statistical tool for studying the distribution of objects of interest in a domain. We study the problem of deploying mobile robots as remote sensors to estimate the parameters of such a model, in particular the intensity parameter λ which measures the mean density of points in a Poisson point process. This problem requires covering an appropriately large section of the domain while avoiding the objects, which we treat as obstacles. We develop a control law that covers an expanding section of the domain and an online criterion for determining when to stop sampling, i.e., when the covered area is large enough to achieve a desired level of estimation accuracy, and illustrate the resulting system with numerical simulations. |

**Acknowledgements** This work was funded in part by the Air Force Office of Scientific Research under the MURI FA9550–10–1−0567, by NRI INSPIRE award 1514882 and by AFRL grant FA865015D1845 (subcontract 669737–1). |