Exploration on continuous Gaussian process frontier maps
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
An information-driven autonomous robotic explo- ration method on a continuous representation of unknown envi- ronments is proposed in this paper. The approach conveniently handles sparse sensor measurements to build a continuous model of the environment that exploits structural dependencies without the need to resort to a fixed resolution grid map. A gradient field of occupancy probability distribution is regressed from sensor data as a Gaussian process providing frontier boundaries for further exploration. The resulting continuous global frontier surface completely describes unexplored regions and, inherently, provides an automatic stop criterion for a desired sensitivity. The performance of the proposed approach is evaluated through simulation results in the well-known Freiburg and Cave maps.
CitationJadidi, M. [et al.]. Exploration on continuous Gaussian process frontier maps. A: IEEE International Conference on Robotics and Automation. "2014 IEEE International Conference on Robotics and Automation (ICRA)". Hong Kong: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 6077-6082.