A Lyapunov-Based Approach to Exploit Asymmetries in Robotic Dual-Arm Task Resolution

Abstract

Dual-arm manipulation tasks can be prescribed to a robotic system in terms of desired absolute and relative motion of the robot's end-effectors. These can represent, e.g., jointly carrying a rigid object or performing an assembly task. When both types of motion are to be executed concurrently, the symmetric distribution of the relative motion between arms prevents task conflicts. Conversely, an asymmetric solution to the relative motion task will result in conflicts with the absolute task. In this work, we address the problem of designing a control law for the absolute motion task together with updating the distribution of the relative task among arms. Through a set of numerical results, we contrast our approach with the classical symmetric distribution of the relative motion task to illustrate the advantages of our method.

Real-Time Kinematically Synchronous Planning for Cooperative Manipulation of Multi-Arms Robot Using the Self-Organizing Competitive Neural Network

“…The cooperative manipulation of robots has been studied a lot. The methods for the cooperative manipulation could be divided into force-based [6][7][8][9] and kinematics-based strategies [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29].…”

“…The movement under the relative motion frame of EEs was studied in [25] for the problem of two-hand assembly. An asymmetric task-planning method based on the Lyapunov theory was proposed in [26] to solve the problems of designing the control law of absolute motion tasks and updating the distribution of relative tasks among arms. Fractional-order derivative and the uncertain fractional-order differential equations were utilized to predict and correct motion trends, and the rationality of the method is verified by different cases [27].…”