This paper presents an interaction control strategy for industrial robot manipulators which consists of the combination of a calibration-free, vision-based control method with an impedancecontrol approach. The vision-based, robot control method known as camera-space manipulation is used to generate a given, previously defined trajectory over an arbitrary surface. Then, a kinematic impedance controller is implemented in order to regulate the interaction forces generated by the contact between the robot end-effector and the work surface where the trajectory is traced. The paper presents experimental evidence on how the vision-force sensory fusion is applied to a path-tracking task, using a Fanuc M16-iB industrial robot equipped with a force/torque sensor at the wrist. In this task, several levels of interaction force between the robot end-effector and the surface were defined. As discussed in the paper, such a synergy between the control schemes is seen as a viable alternative for performing industrial maneuvers that require force modulation between the tool held by the robot and the working surface.
The stiffness controller proposed by Salisbury is an interaction control strategy designed to achieve a desired form of static behavior as regards the interaction of a robot manipulator with the environment. The main idea behind this approach is the simulation of a multidimensional linear spring -or linear elastic material -using the difference between the actual position of the end-effector and a constant position (relaxed point), multiplied by a constant stiffness matrix. In this paper, this idea is generalized with the objective of proposing a controller structure that includes a family of stiffness models based on the idea of linear elastic materials. The new controller structure also includes a damping term in order to have control over energy dissipation, as well as a term added for the purpose of compensating the gravity forces of the links. The stability analysis of the proposed controller was performed in the Lyapunov sense. The new stiffness controller is presented as a case study and compared to other cases, such as the Salisbury controller (Cartesian PD) and the tanh-tanh controller. Experimental results using a three degrees-offreedom direct-drive robot for the evaluation of controllers in a constrained motion task are presented.
A saturating stiffness control scheme for robot manipulators with bounded torque inputs is proposed. The control law is assumed to be a PD-type controller, and the corresponding Lyapunov stability analysis of the closed-loop equilibrium point is presented. The interaction between the robot manipulator and the environment is modeled as spring-like contact forces. The proper behavior of the closed-loop system is validated using a three degree-of-freedom robotic arm.
This paper presents a control strategy for industrial robot manipulators which consists of the combination of a calibration-free, vision-based control method with an impedance control approach. The vision-based, robot control method known as camera-space manipulation is used to generate a given trajectory over an arbitrary surface. Then, a kinematic posture-based impedance controller is implemented in order to regulate the interaction forces generated by the contact between the robot end-effector and the work surface where the trajectory is traced. The paper presents experimental evidence on how the vision-force sensory fusion improves the precision of a robot-interaction task, by using a Fanuc M16-iB industrial robot equipped with a wrist force/torque sensor. As discussed in the paper, such a synergy between the control schemes is seen as a viable alternative for performing industrial maneuvers that require force modulation between the tool held by the robot and the working surface.
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