Imitating human search strategies for assembly

Dennis Ehlers, Markku Suomalainen, Jens Lundell, Ville Kyrki

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

9 Sitaatiot (Scopus)

Abstrakti

We present a Learning from Demonstration method for teaching robots to perform search strategies imitated from humans in scenarios where alignment tasks fail due to position uncertainty. The method utilizes human demonstrations to learn both a state invariant dynamics model and an exploration distribution that captures the search area covered by the demonstrator. We present two alternative algorithms for computing a search trajectory from the exploration distribution, one based on sampling and another based on deterministic ergodic control. We augment the search trajectory with forces learnt through the dynamics model to enable searching both in force and position domains. An impedance controller with superposed forces is used for reproducing the learnt strategy. We experimentally evaluate the method on a KUKA LWR4+ performing a 2D peg-in-hole and a 3D electricity socket task. Results show that the proposed method can, with only few human demonstrations, learn to complete the search task.

AlkuperäiskieliEnglanti
OtsikkoProceedings of the International Conference on Robotics and Automation, ICRA 2019
KustantajaIEEE
Sivut7821-7827
Sivumäärä7
ISBN (elektroninen)9781538660263
DOI - pysyväislinkit
TilaJulkaistu - 1 toukok. 2019
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE International Conference on Robotics and Automation - Montreal, Kanada
Kesto: 20 toukok. 201924 toukok. 2019

Julkaisusarja

NimiIEEE International Conference on Robotics and Automation
KustantajaIEEE
ISSN (painettu)2152-4092
ISSN (elektroninen)2379-9552

Conference

ConferenceIEEE International Conference on Robotics and Automation
LyhennettäICRA
Maa/AlueKanada
KaupunkiMontreal
Ajanjakso20/05/201924/05/2019

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