Mobile Robots as Remote Sensors for Spatial Point Process Models

Loading...
Thumbnail Image
Penn collection
Departmental Papers (ESE)
General Robotics, Automation, Sensing and Perception Laboratory
Kod*lab
Degree type
Discipline
Subject
GRASP
Kodlab
Spatial point processes
remote sensing
mobile robots
coverage
stopping rule
Electrical and Computer Engineering
Engineering
Systems Engineering
Funder
Supported in part by NRI INSPIRE award 1514882 and by AFRL grant FA865015D1845 (subcontract 669737-1).
Grant number
License
Copyright date
Distributor
Contributor
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 lambda 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.

Advisor
Date of presentation
2016-10-01
Conference name
Departmental Papers (ESE)
Conference dates
2023-05-17T15:41:03.000
Conference location
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
missing image.gif
Recommended citation
Collection