TY - GEN
T1 - Experimental validation of domain knowledge assisted robotic exploration and source localization
AU - Wiedemann, Thomas
AU - Shutin, Dmitriy
AU - Lilienthal, Achim J.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/11
Y1 - 2021/8/11
N2 - In situations where toxic or dangerous airborne material is leaking, mobile robots equipped with gas sensors are a safe alternative to human reconnaissance. This work presents the Domain Knowledge Assisted Robotic Exploration and Source Localization (DARES) approach. It allows a multi-robot system to localize multiple sources or leaks autonomously and independently of a human operator. The probabilistic approach builds upon domain knowledge in the form of a physical model of gas dispersion and the a priori assumption that the dispersion process is driven by multiple but sparsely distributed sources. A formal criterion is used to guide the robots to informative measurement locations and enables inference of the source distribution based on gas concentration measurements. Small-scale indoor experiments under controlled conditions are presented to validate the approach. In all three experiments, three rovers successfully localized two ethanol sources.
AB - In situations where toxic or dangerous airborne material is leaking, mobile robots equipped with gas sensors are a safe alternative to human reconnaissance. This work presents the Domain Knowledge Assisted Robotic Exploration and Source Localization (DARES) approach. It allows a multi-robot system to localize multiple sources or leaks autonomously and independently of a human operator. The probabilistic approach builds upon domain knowledge in the form of a physical model of gas dispersion and the a priori assumption that the dispersion process is driven by multiple but sparsely distributed sources. A formal criterion is used to guide the robots to informative measurement locations and enables inference of the source distribution based on gas concentration measurements. Small-scale indoor experiments under controlled conditions are presented to validate the approach. In all three experiments, three rovers successfully localized two ethanol sources.
KW - Bayesian inference
KW - Gas source localization
KW - Mobile robot olfaction
KW - Swarm exploration
UR - http://www.scopus.com/inward/record.url?scp=85117507729&partnerID=8YFLogxK
U2 - 10.1109/ICAS49788.2021.9551145
DO - 10.1109/ICAS49788.2021.9551145
M3 - Conference contribution
AN - SCOPUS:85117507729
T3 - ICAS 2021 - 2021 IEEE International Conference on Autonomous Systems, Proceedings
BT - ICAS 2021 - 2021 IEEE International Conference on Autonomous Systems, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Autonomous Systems, ICAS 2021
Y2 - 11 August 2021 through 13 August 2021
ER -