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 [BibTeX] [Marc21]
A Skill Transfer Approach for Continuum Robots - Imitation of Octopus Reaching Motion with the STIFF-FLOP Robot
Type of publication: Conference paper
Citation: Malekzadeh_AAAI_2014
Publication status: Published
Booktitle: In Proc. of the AAAI Symp. on Knowledge, Skill, and Behavior Transfer in Autonomous Robots
Year: 2014
Month: November
Pages: 49-52
Location: Arlington, VA, USA
URL: http://www.aaai.org/ocs/index....
Abstract: The problem of transferring skills to hyper-redundant system requires the design of new motion primitive representations that can cope with multiple sources of noise and redundancy, and that can dynamically handle perturbations in the environment. One way is to take inspiration from invertebrate systems in nature to seek for new versatile representations of motion/behavior primitives for continuum robots. In particular, the incredibly varied skills achieved by the octopus can guide us toward the design of such robust encoding scheme. This abstract presents our ongoing work that aims at combining statistical machine learning, dynamical systems and stochastic optimization to study the problem of transferring skills to a flexible surgical robot (STIFF-FLOP) composed of 2 modules with constant curvatures. The approach is tested in simulation by imitation and self-refinement of an octopus reaching motion.
Keywords: continuum robots, learning from demonstration, robot learning
Projects Idiap
Authors Malekzadeh, M. S.
Calinon, Sylvain
Bruno, D.
Caldwell, D. G.
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Total mark: 0
  • Malekzadeh_AAAI_2014.pdf