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TROB
2010
129views more  TROB 2010»
14 years 8 months ago
A Probabilistic Particle-Control Approximation of Chance-Constrained Stochastic Predictive Control
—Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation,...
Lars Blackmore, Masahiro Ono, Askar Bektassov, Bri...
ICRA
2007
IEEE
154views Robotics» more  ICRA 2007»
15 years 4 months ago
A Policy for Open-Loop Attenuation of Disturbance Effects Caused by Uncertain Ground Properties in Running
— Outside of the laboratory, accurate models of ground impact dynamics are either difficult or impossible to obtain. Instead, a rigid ground model is often used in gait and cont...
Jonathan W. Hurst, Benjamin Morris, Joel E. Chestn...
AROBOTS
2002
115views more  AROBOTS 2002»
14 years 9 months ago
Statistical Learning for Humanoid Robots
The complexity of the kinematic and dynamic structure of humanoid robots make conventional analytical approaches to control increasingly unsuitable for such systems. Learning techn...
Sethu Vijayakumar, Aaron D'Souza, Tomohiro Shibata...
AAAI
2008
15 years 2 days ago
Adaptive Control for Autonomous Underwater Vehicles
We describe a novel integration of Planning with Probabilistic State Estimation and Execution resulting in a unified representational and computational framework based on declarat...
Conor McGann, Frederic Py, Kanna Rajan, John Ryan,...
IROS
2006
IEEE
157views Robotics» more  IROS 2006»
15 years 3 months ago
Trajectory and Spline Generation for All-Wheel Steering Mobile Robots
We present a method for trajectory generation for all-wheel steering mobile robots which can account for rough terrain and predictable vehicle dynamics and apply it to the problem...
Thomas M. Howard, Alonzo Kelly