Optimal feedback control for anthropomorphic manipulators

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.