—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...
— 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...
The complexity of the kinematic and dynamic structure of humanoid robots make conventional analytical approaches to control increasingly unsuitable for such systems. Learning techn...
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,...
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...