Sensor-Based Estimation and Control of Forces and Moments in Multiple Cooperative Robots

Abstract

Control of multiple robots presents numerous challenges, some of which include synchronization in terms of position, motion, force, load sharing and internal force minimization. This paper presents formulation and application of a fuzzy logic based strategy for control of two 6 degree-of-freedom robots carrying an object in a cooperative mode. The paper focuses on control of internal forces that get generated when two or more robots carry an object in coordination. Force/torque (F/T) sensors mounted on wrist of each robot provide the force and torque data in six dimensions. A fuzzy logic controller has been designed to use these force/torque (F/T) data to achieve a cooperating movement in which one robot acts as leader and the other robot follows. The paper also deals with estimation of external forces acting on end effector with the use of data provided by F/T sensors. These external forces and moments are not directly measured by F/T sensor since the quantities measured by F/T sensor are corrupted by the dynamics of the end effector and manipulator (a F/T sensor is usually mounted between wrist and end effector of the robot). This paper investigates the use of Kalman filtering technique to extract the external forces acting on robot end effector utilizing the underlying dynamics of the end effector. Matlab’s Fuzzy logic, Simulink, and State Flow toolboxes are used for achieving real-time, autonomous and intelligent behavior of the two robots. Simulation results from two separate experiments show that the above strategy was able to constrain the internal forces and provide a smooth movement of the manipulators.