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» Learning Impedance Control for Robotic Manipulators
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ESANN
2004
14 years 11 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»
14 years 11 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...
79
Voted
ICRA
2008
IEEE
185views Robotics» more  ICRA 2008»
15 years 4 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
95
Voted
AAAI
2011
13 years 9 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»
15 years 4 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...