Kinematically optimised predictions of object motion

Dominik Belter, Marek Kopicki, Sebastian Zurek, Jeremy Wyatt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Predicting the motions of rigid objects under contacts is a necessary precursor to planning of robot manipulation of objects. On the one hand physics based rigid body simulations are used, and on the other learning approaches are being developed. The advantage of physics simulations is that because they explicitly perform collision checking they respect kinematic constraints, producing physically plausible predictions. The advantage of learning approaches is that they can capture the effects on motion of unobservable parameters such as mass distribution, and frictional coefficients, thus producing more accurate predicted trajectories. This paper shows how to bring together the advantages of both approaches to achieve learned simulators of specific objects that outperform previous learning approaches. Our approach employs a fast simplified collision checker and a learning method. The learner predicts trajectories for the object. These are optimised post prediction to minimise interpenetrations according to the collision checker. In addition we show that cleaning the training data prior to learning can also improve performance. Combining both approaches results in consistently strong prediction performance. The new simulator outperforms previous learning based approaches on a single contact push manipulation prediction task. We also present results showing that the method works for multi-contact manipulation, for which rigid body simulators are notoriously unstable.

Original languageEnglish
Title of host publicationIEEE International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages4422-4427
Number of pages6
ISBN (Print)9781479969340
DOIs
Publication statusPublished - 31 Oct 2014
Event2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 - Chicago, United States
Duration: 14 Sep 201418 Sep 2014

Conference

Conference2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
Country/TerritoryUnited States
CityChicago
Period14/09/1418/09/14

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Kinematically optimised predictions of object motion'. Together they form a unique fingerprint.

Cite this