PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Optimal Feedback Control for Anthropomorphic Manipulators
Djordje Mitrovic, Sho Nagashima, Stefan Klanke, Takamitsu Matsubara and Sethu Vijayakumar
In: ICRA 2010, Anchorage, Alaska, USA(2010).

Abstract

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 Optimal Feedback Control (OFC) by introducing a specific cost function that accounts for the physical constraints of the controlled plant. Using an approximative computational optimal control method we can optimally control a high-dimensional anthropomorphic robot without having to specify an explicit inverse kinematics, inverse dynamics or feedback control law. We highlight the benefits of this biologically plausible motor control strategy over traditional (open loop) optimal controllers: The presented approach proves to be significantly more energy efficient and compliant, while being accurate with respect to the task at hand. These properties are crucial for the control of mobile anthropomorphic robots, that are designed to interact safely in a human environment. To the best of our knowledge this is the first OFC implementation on a high-dimensional (redundant) manipulator.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5897
Deposited By:Stefan Klanke
Deposited On:08 March 2010