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EUSFLAT
2001

Adaptive torque control using a connectionist reinforcement learning agent

8 years 5 months ago
Adaptive torque control using a connectionist reinforcement learning agent
The correction of angular misalignment between mating components is a fundamental requirement for their successful assembly. In this paper we present how a learning agent based on the Stochastic Gradient Ascent (SGA) algorithm can be used to command appropriate rotations of a robotic manipulator's hand in order to minimise such misalignments and allow the completion of a peg in hole task. The learning capabilities of the proposed methodology are proven both with simulation and real time implementation using a PUMA 6 DOF industrial manipulator.
Lorenzo Brignone, Martin Howarth, S. Sivayoganatha
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2001
Where EUSFLAT
Authors Lorenzo Brignone, Martin Howarth, S. Sivayoganathan, V. Balendran
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