TY - GEN
T1 - The DustBot system
T2 - Using mobile robots to monitor pollution in pedestrian area
AU - Reggente, Matteo
AU - Mondini, Alessio
AU - Ferri, Gabriele
AU - Mazzolai, Barbara
AU - Manzi, Alessandro
AU - Gabelletti, Matteo
AU - Dario, Paolo
AU - Lilienthal, Achim J.
PY - 2010
Y1 - 2010
N2 - The EU project DustBot addresses urban hygiene. Two types of robots were designed, the DustClean robot to autonomously clean pedestrian areas, and the DustCart robot for door-to-door garbage collection. Three prototype robots were built and equipped with electronic noses so as to enable them to collect environmental data while performing their urban hygiene tasks. Essentially, the robots act as a mobile, wireless node in a sensor network. In this paper we give an overview of the DustBot platform focusing on the Air Monitoring Module (AMM). We describe the data flow between the robots through the ubiquitous network to a gas distribution modelling server, where a gas distribution model is computed. We describe the Kernel DM+V algorithm, an approach to create statistical gas distribution models in the form of predictive mean and variance discretized onto a grid map. Finally we present and discuss results obtained with the DustBot AMM during experimental trials performed in outdoor public places: a courtyard in Pontedera, Italy and a pedestrian square in Örebro, Sweden.
AB - The EU project DustBot addresses urban hygiene. Two types of robots were designed, the DustClean robot to autonomously clean pedestrian areas, and the DustCart robot for door-to-door garbage collection. Three prototype robots were built and equipped with electronic noses so as to enable them to collect environmental data while performing their urban hygiene tasks. Essentially, the robots act as a mobile, wireless node in a sensor network. In this paper we give an overview of the DustBot platform focusing on the Air Monitoring Module (AMM). We describe the data flow between the robots through the ubiquitous network to a gas distribution modelling server, where a gas distribution model is computed. We describe the Kernel DM+V algorithm, an approach to create statistical gas distribution models in the form of predictive mean and variance discretized onto a grid map. Finally we present and discuss results obtained with the DustBot AMM during experimental trials performed in outdoor public places: a courtyard in Pontedera, Italy and a pedestrian square in Örebro, Sweden.
UR - http://www.scopus.com/inward/record.url?scp=78650374726&partnerID=8YFLogxK
U2 - 10.3303/CET1023046
DO - 10.3303/CET1023046
M3 - Conference contribution
AN - SCOPUS:78650374726
SN - 9788895608143
VL - 23
SP - 273
EP - 278
BT - NOSE2010 - International Conference on Environmental Odour Monitoring and Control
PB - Italian Association of Chemical Engineering - AIDIC
ER -