Sparse Control of Robot Grasping from 2D Subspaces

Aggeliki Tsoli, Odest Chadwicke Jenkins



Abstract

Human control of high degree-of-freedom robotic systems is often difficult due to the overwhelming number of variables that need to be specified. Instead, we propose the use of sparse subspaces embedded within the pose space of a robotic system. Driven by human motion, we addressed this sparse control problem by uncovering 2D subspaces that allow cursor control, or eventually decoding of neural activity, to drive a robotic hand. Considering the problems in previous work related to noise in pose graph construction and motion capture, we introduced a method for denoising neighborhood graphs for embedding hand motion into 2D spaces. Such spaces allow for control of high-DOF systems using 2D interfaces such as cursor control via mouse or decoding of neural activity. We present results demonstrating our approach to interactive sparse control for successful power grasping and precision grasping using a 13 DOF robot hand.


Videos

Mouse driven control of the DLR Hand [Video(high/medium/low)]


Publications

A. Tsoli, and O. C. Jenkins. Neighborhood denoising for learning high-dimensional grasping manifolds. In International Conference on Intelligent RObots and Systems (IROS 2008), Nice, France, September 2008. To appear.
[.bib| .pdf]

A. Tsoli, and O. C. Jenkins. Robot grasping for prosthetic applications. In 13th International Symposium of Robotics Research (ISRR 2007), Hiroshima, Japan, November 2007.
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A. Tsoli, and O. C. Jenkins. Cursor-controlled prosthetic grasping from 2D subspaces. In MAIA Workshop 'BCI Meets Robotics: Challenging Issues in Brain-Computer Interaction and Shared Control', Leuven, Belgium, November 2007.
[.bib | .pdf]

A. Tsoli, and O. C. Jenkins. 2D subspaces for user-driven robot grasping. In RSS 2007 workshop on Robot Manipulation: Sensing and Adapting to the Real World, Atlanta, GA, USA, June 2007.
[.bib | .pdf]

O. C. Jenkins. 2D subspaces for sparse control of high-dof robots. In Intl. Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2006), New York, NY, USA, Aug-Sep 2006.
[ .bib | .pdf ]

S.-P. Kim, J. Simeral, O. Jenkins, J. Donoghue, and M. Black. Finding directional movement representations in motor cortical neural populations using nonlinear manifold learning. In World Congress on Medical Physics and Biomedical Engineering 2006, Seoul, Korea, aug 2006.
[ .bib | .pdf ]


Sponsors

ONR DURIP, ``Neural Interfaces to Enhance Human Motor Performance: Instrumentation for Modeling Dexterous Manipulation''