Bae, Ji-Hun Kim, Doik 2024-01-20T10:32:06Z 2024-01-20T10:32:06Z 2021-09-05 2014-02 1598-6446 https://pubs.kist.re.kr/handle/201004/127141 Many tasks assigned to a manipulator include interactions with its operating environment or manipulating objects, which are detected as forces and moments by the force sensor. It is, however, not easy to detect when a pure external wrench occurred in interactions or manipulations since signals measured by the force sensor consist of the inertial effect of the end-effector and manipulating objects as well as the effect of interactions. In order to separate these combined effects, a self-classification method for the 6-axis force sensor is proposed in this paper by relating the wrench and the virtual point mass. With the proposed method, wrenches due to the end-effector and objects can be classified in run-time without any prior information for them, and thus a pure external wrench can also be distinguished from them. The effectiveness of the proposed self-classification method is verified through experiments. English INST CONTROL ROBOTICS & SYSTEMS, KOREAN INST ELECTRICAL ENGINEERS SENSOR FUSION Run-time Self-classification of External Force using Virtual Point Mass Approximation for Object Manipulation Article 10.1007/s12555-012-0538-7 1 INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, v.12, no.1, pp.137 - 146 INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 12 1 137 146 scie scopus kci ART001846502 000330415900016 2-s2.0-84896790798 Automation & Control Systems Automation & Control Systems Article SENSOR FUSION Classification of external force force sensor object manipulation virtual point mass wrench