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Statistical visual-dynamic model for hand-eye coordination


Reference:

Beale, D., Iravani, P. and Hall, P., 2010. Statistical visual-dynamic model for hand-eye coordination. In: IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings. Piscataway, NJ: IEEE Computer Society, pp. 3931-3936.

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Official URL:

http://dx.doi.org/10.1109/IROS.2010.5648832

Abstract

This paper introduces a new statistical method for combining vision and robot dynamics to generate trajectories to intercept a moving object. Previous methods only use information from the kinematics without considering the forces needed to move along the trajectory. Using robot dynamics allows extra measures, such as energy efficiency, to be optimised alongside maximising the likelihood of intercepting the target. We derive a statistical model for a vision system and a Lagrangian dynamical model of a robotic arm, showing how to relate joint torques to the vision. The method is tested by applying it to the problem of catching a simulated moving object.

Details

Item Type Book Sections
CreatorsBeale, D., Iravani, P. and Hall, P.
DOI10.1109/IROS.2010.5648832
DepartmentsFaculty of Engineering & Design > Mechanical Engineering
Faculty of Science > Computer Science
StatusPublished
ID Code22617
Additional Information23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010. 18-22 October 2010. Taipei, Taiwan. ID number: 5648832

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