Imperial College London

Dr Thrishantha Nanayakkara

Faculty of EngineeringDyson School of Design Engineering

Reader in Design Engineering and Robotics
 
 
 
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Contact

 

+44 (0)20 7594 0965t.nanayakkara Website CV

 
 
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Location

 

RCS1 M229Dyson BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Song:2014:10.1109/TRO.2013.2279630,
author = {Song, X and Liu, H and Althoefer, K and Nanayakkara, T and Seneviratne, LD},
doi = {10.1109/TRO.2013.2279630},
journal = {IEEE Transactions on Robotics},
pages = {203--219},
title = {Efficient break-away friction ratio and slip prediction based on haptic surface exploration},
url = {http://dx.doi.org/10.1109/TRO.2013.2279630},
volume = {30},
year = {2014}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - The break-away friction ratio (BF-ratio), which is the ratio between friction force and the normal force at slip occurrence, is important for the prediction of incipient slip and the determination of optimal grasping forces. Conventionally, this ratio is assumed constant and approximated as the static friction coefficient. However, this ratio varies with acceleration rates and force rates applied to the grasped object and the object material, which lead to difficulties in determining optimal grasping forces that avoid slip. In this paper, we propose a novel approach based on the interactive forces to allow a robotic hand to predict object slip before its occurrence. The approach only requires the robotic hand to have a short haptic surface exploration over the object surface before manipulating it. Then, the frictional properties of the finger-object contact can be efficiently identified, and the BF-ratio can be real-time predicted to predict slip occurrence under dynamic grasping conditions. Using the predicted BF-ratio as a slip, threshold is demonstrated to be more accurate than using the static/Coulomb friction coefficient. The presented approach has been experimentally evaluated on different object surfaces, showing good performance in terms of prediction accuracy, robustness, and computational efficiency. © 2013 IEEE.
AU - Song,X
AU - Liu,H
AU - Althoefer,K
AU - Nanayakkara,T
AU - Seneviratne,LD
DO - 10.1109/TRO.2013.2279630
EP - 219
PY - 2014///
SN - 1552-3098
SP - 203
TI - Efficient break-away friction ratio and slip prediction based on haptic surface exploration
T2 - IEEE Transactions on Robotics
UR - http://dx.doi.org/10.1109/TRO.2013.2279630
VL - 30
ER -