ICRA 2023poster5 citations

Proprioceptive Sensor-Based Simultaneous Multi-Contact Point Localization and Force Identification for Robotic Arms

Seo Wook Han, Min Jun Kim

Abstract

In this paper, we propose an algorithm that estimates contact point and force simultaneously. We consider a collaborative robot equipped with proprioceptive sensors, in particular, joint torque sensors (JTSs) and a base force/torque (F/T) sensor. The proposed method has the following advan-tages. First, fast computation is achieved by proper preprocessing of robot meshes. Second, multi-contact can be identified with the aid of the base F/T sensor, while this is challenging when the robot is equipped with only JTSs. The proposed method is a modification of the standard particle filter to cope with mesh preprocessing and with available sensor data. In simulation validation, for a 7 degree-of-freedom robot, the algorithm runs at 2200Hz with 99.96% success rate for the single-contact case. In terms of the run-time, the proposed method was ≥3.5X faster compared to the existing methods. Dual and triple contacts are also reported in the manuscript.

BibTeX
@inproceedings{icra2023_proprioceptivese,
  title = {Proprioceptive Sensor-Based Simultaneous Multi-Contact Point Localization and Force Identification for Robotic Arms},
  author = {Seo Wook Han and Min Jun Kim},
  booktitle = {ICRA 2023},
  year = {2023}
}
Proprioceptive Sensor-Based Simultaneous Multi-Contact Point Localization and Force Identification for Robotic Arms · ICRA 2023