Improvement of Force Control in Robotic Manipulators Using Sensor Fusion Techniques

Abstract

In the never-ending effort of the humanity to simplify their existence, the introduction of ‘intelligent’ resources was inevitable to come (IFR, 2001). One characteristic of these ‘intelligent’ systems is their ability to adapt themselves to the variations in the outside environment as the internal changes occurring within the system. Thus, the robustness of an ‘intelligent’ system can be measured in terms of the sensitivity and adaptability to such internal and external variations. In this sense, robot manipulators could be considered as ‘intelligent’ systems; but for a robotic manipulator without sensors explicitly measuring positions or contact forces acting at the end-effector, the robot TCP has to follow a path in its workspace without regard to any feedback other than its joints shaft encoders or resolvers. This restrictive fact imposes severe limitations on certain tasks where an interaction between the robot and the environment is needed. However, with the help of sensors, a robot can exhibit an adaptive behaviour (Harashima and Dote, 1990), the robot being able to deal flexibly with changes in its environment and to execute complicated skilled tasks. On the other hand, the manipulation can be controlled only after the interaction forces are managed properly. That is why force control is required in manipulation robotics. For the force control to be implemented, information regarding forces at the contact point has to be fed back to the controller and force/torque (F/T) sensors can deliver that information. But an important problem arises when we have only a force sensor. That is a dynamic problem: in the dynamic situation, not only the interaction forces and moments at the contact point but also the inertial forces of the tool mass are measured by the wrist force sensor (Gamez et al., 2008b). In addition, the magnitude of these dynamics forces cannot be ignored when large accelerations and fast motions are considered (Khatib, 1987). Since the inertial forces are perturbation forces to be measured or estimated in the robot manipulation, we need to process the force sensor signal in order to extract the contact force exerted by the robot. Previous results, related to contact force estimation, can be found in (Uchiyama, 1979), (Uchiyama and Kitagaki, 1989) and (Lin, 1997). In all the cases, the dynamic information of the tool was considered but some of the involved variables, such as the acceleration of the tool, were simply estimated by means of the kinematic model of the manipulator. However, these estimations did not reflect the real acceleration of the tool and thus high accuracy