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Conference Paper

A unifying methodology for the control of robotic systems


Peters,  J
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Peters, J., Mistry M, Udwadia FE, Cory R, Nakanishi, J., & Schaal, S. (2005). A unifying methodology for the control of robotic systems. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005) (pp. 1824-1831). Piscataway, NJ, USA: IEEE Operations Center.

Cite as:
Recently, R. E. Udwadia (2003) suggested to derive tracking controllers for mechanical systems using a generalization of Gausslsquo; principle of least constraint. This method allows us to reformulate control problems as a special class of optimal control. We take this line of reasoning one step further and demonstrate that well-known and also several novel nonlinear robot control laws can be derived from this generic methodology. We show experimental verifications on a Sarcos Master Arm robot for some of the derived controllers. We believe that the suggested approach offers a promising unification and simplification of nonlinear control law design for robots obeying rigid body dynamics equations, both with or without external constraints, with over-actuation or underactuation, as well as open-chain and closed-chain kinematics.