Presentado al Robotics: Science and Systems: Workshop on Robotic Exploration, Monitoring, and Information Collection celebrado en Berlin del 24 al 28 de junio de 2013. ; In this paper, a novel solution for autonomous robotic exploration is proposed. The distribution of information in an unknown environment is modeled as an unsteady diffusion process, which can be an appropriate mathematical formulation and analogy for expanding, time-varying, and dynamic environments. This information distribution map is the solution of the diffusion process partial differential equation, and is regressed from sensor data as a Gaussian Process. Optimization of the process parameters leads to an optimal frontier map which describes regions of interest for further exploration. Since the presented approach considers a continuous model of the environment, it can be used to plan smooth exploration paths exploiting the structural dependencies of the environment whilst handling sparse sensors measurements. The performance of the proposed approach is evaluated through simulation results in the well-known Freiburg and Cave maps. ; J. Andrade acknowledges support from the Spanish Ministry of Economy and Competitiveness project PAU+ DPI 2011-27510 and the EU FP7 project ARCAS ICT-287617. R. Valencia acknowledges support from the EU FP7 project SPENCER ICT-600877. ; Peer Reviewed
Exploration in information distribution maps
2013-01-01
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
DDC: | 629 |
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