Analytic grasp success prediction with tactile feedback
2016 (English)In: Proceedings - IEEE International Conference on Robotics and Automation, Institute of Electrical and Electronics Engineers (IEEE), 2016, 165-171 p.Conference paper (Refereed)
Predicting grasp success is useful for avoiding failures in many robotic applications. Based on reasoning in wrench space, we address the question of how well analytic grasp success prediction works if tactile feedback is incorporated. Tactile information can alleviate contact placement uncertainties and facilitates contact modeling. We introduce a wrench-based classifier and evaluate it on a large set of real grasps. The key finding of this work is that exploiting tactile information allows wrench-based reasoning to perform on a level with existing methods based on learning or simulation. Different from these methods, the suggested approach has no need for training data, requires little modeling effort and is computationally efficient. Furthermore, our method affords task generalization by considering the capabilities of the grasping device and expected disturbance forces/moments in a physically meaningful way.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. 165-171 p.
Proceedings - IEEE International Conference on Robotics and Automation, ISSN 1050-4729
Forecasting Tools Uncertainty analysis Based reasonings Computationally efficient Contact modeling Disturbance force Robotic applications Tactile feedback Tactile information Training data
IdentifiersURN: urn:nbn:se:kth:diva-194529DOI: 10.1109/ICRA.2016.7487130ISI: 000389516200024ScopusID: 2-s2.0-84977515559ISBN: 978-1-4673-8026-3OAI: oai:DiVA.org:kth-194529DiVA: diva2:1043814
2016 IEEE International Conference on Robotics and Automation, ICRA 2016, 16 May 2016 through 21 May 2016
FunderKnut and Alice Wallenberg Foundation
QC 201611012016-11-012016-10-312017-01-19Bibliographically approved