Active Exploration Using Gaussian Random Fields and Gaussian Process Implicit Surfaces
2016 (English)In: 2016 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2016), Institute of Electrical and Electronics Engineers (IEEE), 2016, 582-589 p.Conference paper (Refereed)
In this work we study the problem of exploring surfaces and building compact 3D representations of the environment surrounding a robot through active perception. We propose an online probabilistic framework that merges visual and tactile measurements using Gaussian Random Field and Gaussian Process Implicit Surfaces. The system investigates incomplete point clouds in order to find a small set of regions of interest which are then physically explored with a robotic arm equipped with tactile sensors. We show experimental results obtained using a PrimeSense camera, a Kinova Jaco2 robotic arm and Optoforce sensors on different scenarios. We then demostrate how to use the online framework for object detection and terrain classification.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. 582-589 p.
Active perception, Surface reconstruction, Gaussian process, Implicit surface, Random field, Tactile exploration
IdentifiersURN: urn:nbn:se:kth:diva-202672DOI: 10.1109/IROS.2016.7759112ISI: 000391921700086ScopusID: 2-s2.0-85006371409ISBN: 978-1-5090-3762-9 OAI: oai:DiVA.org:kth-202672DiVA: diva2:1078703
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), OCT 09-14, 2016, Daejeon, SOUTH KOREA
QC 201703062017-03-062017-03-062017-03-06Bibliographically approved