Correspondence Mapping Induced State and Action Metrics for Robotic Imitation

• Published in: IEEE transactions on cybernetics 2007-04, Vol.37 (2), p.299-307
• Main Authors: Alissandrakis, A., Nehaniv, C.L., Dautenhahn, K.
• Format: Article
• Language: English
• Subjects: Algorithms; Artificial Intelligence; Biomimetics - methods; Computer science; Computer Simulation; Correspondence problem; Cybernetics; Cybernetics - methods; Degrees of freedom; Education; Humans; imitation and social learning; Imitative Behavior - physiology; Kinematics; Mapping; Mathematical analysis; Mathematical models; Mirrors; Models, Biological; Morphology; Movement - physiology; p rogramming by demonstration; Pediatrics; Psychology; Robot kinematics; Robot programming; Robotics; Robotics - methods; state and action metrics; Symmetric matrices; Task Performance and Analysis
• ISSN: 1083-4419; 2168-2267; 1941-0492; 2168-2275
• DOI: 10.1109/TSMCB.2006.886947

This paper addresses the problem of body mapping in robotic imitation where the demonstrator and imitator may not share the same embodiment [degrees of freedom (DOFs), body morphology, constraints, affordances, and so on]. Body mappings are formalized using a unified (linear) approach via correspondence matrices, which allow one to capture partial, mirror symmetric, one-to-one, one-to-many, many-to-one, and many-to-many associations between various DOFs across dissimilar embodiments. We show how metrics for matching state and action aspects of behavior can be mathematically determined by such correspondence mappings, which may serve to guide a robotic imitator. The approach is illustrated and validated in a number of simulated 3-D robotic examples, using agents described by simple kinematic models and different types of correspondence mappings