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» Learning Impedance Control for Robotic Manipulators
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ESANN
2004
13 years 8 months ago
A sliding mode controller using neural networks for robot manipulator
Abstract. This paper proposes a new sliding mode controller using neural networks. Multilayer neural networks with the error back-propagation learning algorithm are used to compens...
Hajoon Lee, Dongkyung Nam, Cheol Hoon Park
EUSFLAT
2001
144views Fuzzy Logic» more  EUSFLAT 2001»
13 years 8 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...
Lorenzo Brignone, Martin Howarth, S. Sivayoganatha...
ICRA
2008
IEEE
185views Robotics» more  ICRA 2008»
14 years 1 months ago
Humanoid teleoperation for whole body manipulation
— We present results of successful telemanipulation of large, heavy objects by a humanoid robot. Using a single joystick the operator controls walking and whole body manipulation...
Mike Stilman, Koichi Nishiwaki, Satoshi Kagami
AAAI
2011
12 years 6 months ago
Autonomous Skill Acquisition on a Mobile Manipulator
We describe a robot system that autonomously acquires skills through interaction with its environment. The robot learns to sequence the execution of a set of innate controllers to...
George Konidaris, Scott Kuindersma, Roderic A. Gru...
ICRA
2009
IEEE
116views Robotics» more  ICRA 2009»
14 years 1 months ago
A new framework for force feedback teleoperation of robotic vehicles based on optical flow
— This paper proposes the use of optical flow from a moving robot to provide force feedback to an operator’s joystick to facilitate collision free teleoperation. Optic flow i...
Robert E. Mahony, Felix Schill, Peter I. Corke, Yo...