Constructive incremental learning from only local information
Neural Computation
Optimal trajectory formation of constrained human arm reaching movements
Biological Cybernetics
A unifying framework for robot control with redundant DOFs
Autonomous Robots
Learning to Control in Operational Space
International Journal of Robotics Research
Robust constraint-consistent learning
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
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Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently change between contexts. In this paper, we present a novel approach for learning (unconstrained) control policies from movement data, where observations come from movements under different constraints. As a key ingredient, we introduce a small but highly effective modification to the standard risk functional, allowing us to make a meaningful comparison between the estimated policy and constrained observations. We demonstrate our approach on systems of varying complexity, including kinematic data from the ASIMO humanoid robot with 27 degrees of freedom.