Now showing items 1-5 of 5
Optimal Feedback Control for Anthropomorphic Manipulators
We study target reaching tasks of redundant anthropomorphic manipulators under the premise of minimal energy consumption and compliance during motion. We formulate this motor control problem in the framework of ...
Adaptive Optimal Feedback Control with Learned Internal Dynamics Models
Optimal Feedback Control (OFC) has been proposed as an attractive movement generation strategy in goal reaching tasks for anthropomorphic manipulator systems. Recent developments, such as the Iterative Linear Quadratic ...
Transferring Impedance Control Strategies Between Heterogeneous Systems via Apprenticeship Learning
We present a novel method for designing controllers for robots with variable impedance actuators. We take an imitation learning approach, whereby we learn impedance modulation strategies from observations of behaviour (for ...
A Computational Model of Limb Impedance Control Based on Principles of Internal Model Uncertainty
Efficient human motor control is characterized by an extensive use of joint impedance modulation, which is achieved by co-contracting antagonistic muscles in a way that is beneficial to the specific task. While there is ...
Stochastic optimal control with learned dynamics models
(The University of Edinburgh, 2011)
The motor control of anthropomorphic robotic systems is a challenging computational task mainly because of the high levels of redundancies such systems exhibit. Optimality principles provide a general strategy to resolve ...