Task-Space Consensus of Networked Robotic Systems: Separation and Manipulability
For researchers in multi-robot coordination, this work provides a method to achieve consensus while quantifying manipulability, though it is an incremental extension of existing adaptive control and consensus techniques.
This paper addresses task-space consensus for networked robotic systems with uncertain kinematics and dynamics, proposing an observer-based adaptive controller that achieves manipulable consensus without task-space velocity measurements. Simulations demonstrate the controller's effectiveness.
In this paper, we investigate the task-space consensus problem for multiple robotic systems with both the uncertain kinematics and dynamics and address two main issues, i.e., the separation of the kinematic and dynamic loops in the case of no task-space velocity measurement and the quantification of the manipulability of the system. We propose an observer-based adaptive controller to achieve the manipulable consensus without relying on the measurement of task-space velocities, and also formalize the concept of manipulability to quantify the degree of adjustability of the consensus value. The proposed adaptive controller employs a new distributed observer that does not rely on the joint velocity and a new kinematic parameter adaptation law with a distributed adaptive kinematic regressor matrix that is driven by both the observation and consensus errors. In addition, it is shown that the proposed controller has the separation property, which yields an adaptive kinematic controller that is applicable to most industrial/commercial robots. The performance of the proposed observer-based adaptive schemes is shown by numerical simulations.