Towards Manipulability of Interactive Lagrangian Systems
This work addresses the challenge of designing controllers for interactive robotic systems like teleoperation and teaching, offering a unified paradigm that balances network coupling and dynamics, though it appears incremental in extending existing adaptive control methods.
The paper tackles the problem of ensuring infinite manipulability in interactive Lagrangian systems with parametric uncertainty and communication constraints, proposing adaptive controllers that achieve this property and robustness, including a solution for nonlinear bilateral teleoperation with arbitrary unknown time-varying delay.
This paper investigates manipulability of interactive Lagrangian systems with parametric uncertainty and communication/sensing constraints. Two standard examples are teleoperation with a master-slave system and teaching operation of robots. We here systematically formulate the concept of infinite manipulability for general dynamical systems, and investigate how such a unified motivation yields a design paradigm towards guaranteeing the infinite manipulability of interactive dynamical systems and in particular facilitates the design and analysis of nonlinear adaptive controllers for interactive Lagrangian systems. Specifically, based on a new class of dynamic feedback, we propose adaptive controllers that achieve both the infinite manipulability of the controlled Lagrangian systems and the robustness with respect to the communication/sensing constraints, mainly owing to the resultant dynamic-cascade framework. The proposed paradigm yields the desirable balance between network coupling requirements and controlled dynamics of human-system interaction. We also show that a special case of our main result resolves the longstanding nonlinear bilateral teleoperation problem with arbitrary unknown time-varying delay. Simulation results show the performance of the interactive robotic systems under the proposed adaptive controllers.