Being able to perform dynamic motions repeatably and reliably is an active research topic. The present thesis aims to contribute to this by improving the accuracy of force-torque sensing in robots. It focuses primarily on six axis force-torque sensors, although other sources of force-torque sensing are explored. Force sensing technologies, calibration procedures of these sensors and the use of force-torque sensing in robotics are described with the aim to familiarize the reader with the problem to solve. The problem is tackled in two ways: improving the accuracy of six axis force-torque sensors and exploring the use of tactile sensor arrays as force-torque sensors. The contributions of this thesis are : the development of the Model Based In situ calibration method for improving measurements of sensors already mounted on robots and the improvement in performance of the robot as a consequence; the design of a calibration device to improve the reliability and speed of calibration; and the improvement of force sensing information of a capacitive tactile array and its use on a robot as force-torque information source. The developed algorithms were tested on the humanoid robotic platform iCub.
Force-Torque Sensing in Robotics
2019-04-08
doi:10.15167/andrade-chavez-francisco-javier_phd2019-04-08
Theses
Electronic Resource
English
DDC: | 629 |
Force feedback exploiting tactile and proximal force/torque sensing
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