Probabilistic balance monitoring for bipedal robots

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dc.identifier.uri http://dx.doi.org/10.15488/3041
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/3071
dc.contributor.author Höhn, O.
dc.contributor.author Gerth, W.
dc.date.accessioned 2018-03-01T12:59:32Z
dc.date.available 2018-03-01T12:59:32Z
dc.date.issued 2009
dc.identifier.citation Höhn, O.; Gerth, W.: Probabilistic balance monitoring for bipedal robots. In: International Journal of Robotics Research 28 (2009), Nr. 2, S. 245-256. DOI: https://doi.org/10.1177/0278364908095170
dc.description.abstract In this paper, a probability-based balance monitoring concept for humanoid robots is proposed. Two algorithms are presented that allow us to distinguish between exceptional situations and normal operations. The first classification approach uses Gaussian-Mixture-Models (GMM) to describe the distribution of the robot's sensor data for typical situations such as stable walking or falling down. With the GMM it is possible to state the probability of the robot being in one of the known situations. The concept of the second algorithm is based on Hidden-Markov-Models (HMM). The objective is to detect and classify unstable situations by means of their typical sequences in the robot's sensor data. When appropriate reflex motions are linked to the critical situations, the robot can prevent most falls or is at least able to execute a controlled falling motion. The proposed algorithms are verified by simulations and experiments with our bipedal robot BARt-UH. © SAGE Publications 2009 Los Angeles, London. eng
dc.language.iso eng
dc.publisher London : SAGE Publications Ltd.
dc.relation.ispartofseries International Journal of Robotics Research 28 (2009), Nr. 2
dc.rights Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. Dieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
dc.subject Balance monitoring eng
dc.subject Classification eng
dc.subject Fall detection eng
dc.subject HMM eng
dc.subject Reflex motions eng
dc.subject Robot eng
dc.subject Viability kernel eng
dc.subject Balance monitoring eng
dc.subject Classification eng
dc.subject Fall detection eng
dc.subject HMM eng
dc.subject Reflex motions eng
dc.subject Robot eng
dc.subject Viability kernel eng
dc.subject Hidden Markov models eng
dc.subject Magnetostrictive devices eng
dc.subject Robotics eng
dc.subject Sensors eng
dc.subject Robots eng
dc.subject.ddc 620 | Ingenieurwissenschaften und Maschinenbau ger
dc.title Probabilistic balance monitoring for bipedal robots
dc.type article
dc.type Text
dc.relation.issn 0278-3649
dc.relation.doi https://doi.org/10.1177/0278364908095170
dc.bibliographicCitation.issue 2
dc.bibliographicCitation.volume 28
dc.bibliographicCitation.firstPage 245
dc.bibliographicCitation.lastPage 256
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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