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Experimental Validation of Domain Knowledge Assisted Robotic Exploration and Source Localization

Thomas Wiedemann, Dmitriy Shutin, Achim J. Lilienthal

发表年份
2021
引用次数
6

摘要

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.

关键词

A priori and a posterioriRobotComputer scienceProbabilistic logicInferenceDomain (mathematical analysis)Mobile robotArtificial intelligenceDomain knowledgeProcess (computing)

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