Optimal geometric structures of force/torque sensors
International Journal of Robotics Research
Fundamentals of Manipulator Calibration
Fundamentals of Manipulator Calibration
Force Sensing Using Kalman Filtering Techniques for Robot Compliant Motion Control
Journal of Intelligent and Robotic Systems
Robotics and Computer-Integrated Manufacturing
Improvement of vision guided robotic accuracy using Kalman filter
Computers and Industrial Engineering
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In the robotic manipulation context, end-effector contact forces may be difficult to measure mainly due to the tool dynamic interferences such as the inertial forces. In this paper, a whole methodology is proposed to estimate these forces. The new approach is based on a sensor fusion technique that integrates the information of a wrist force sensor, of a 3D accelerometer placed at the robot tool and the joint position sensors measurements. The proposed methodology not only offers a suitable estimator in terms of response and filtering, but also presents a self-calibrating feature that allows an easy integration into any industrial setup. To experimentally validate the performance of the proposed methodology, two different industrial manipulators were used: an ABB robot and a Staubli robot, both with open control system architectures. An impedance control scheme was used as force/position control law to demonstrate the need and results of the proposed calibration result.