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» Learning to Control in Operational Space
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ICRA
2009
IEEE
116views Robotics» more  ICRA 2009»
15 years 10 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...
CORR
2011
Springer
188views Education» more  CORR 2011»
14 years 11 months ago
Information-Theoretic Viewpoints on Optimal Causal Coding-Decoding Problems
—In this paper we consider an interacting two-agent sequential decision-making problem consisting of a Markov source process, a causal encoder with feedback, and a causal decoder...
Siva K. Gorantla, Todd P. Coleman
CEC
2010
IEEE
15 years 5 months ago
Adaptive learning particle swarm optimizer-II for global optimization
This paper presents an updated version of the adaptive learning particle swarm optimizer (ALPSO) [6], we call it ALPSO-II. In order to improve the performance of ALPSO on multi-mod...
Changhe Li, Shengxiang Yang
ICRA
2010
IEEE
170views Robotics» more  ICRA 2010»
15 years 2 months ago
Superhuman performance of surgical tasks by robots using iterative learning from human-guided demonstrations
In the future, robotic surgical assistants may assist surgeons by performing specific subtasks such as retraction and suturing to reduce surgeon tedium and reduce the duration of s...
Jur van den Berg, Stephen Miller, Daniel Duckworth...
ACL
2011
14 years 7 months ago
Learning to Win by Reading Manuals in a Monte-Carlo Framework
This paper presents a novel approach for leveraging automatically extracted textual knowledge to improve the performance of control applications such as games. Our ultimate goal i...
S. R. K. Branavan, David Silver, Regina Barzilay