Research of current studying status and developing trend of decoupling algorithm for six-axis force/torque sensor
Binbin Han, Yingjun Li, Guicong Wang
Available Online November 2016.
- https://doi.org/10.2991/aest-16.2016.85How to use a DOI?
- six-axis force sensor; decoupling algorithm; genetic algorithm; neural network.
- For different structures of sensor have many decoupling algorithms, this paper discusses mainly from two aspects the decoupling algorithm of six-axis force/torque sensor. One is the linear decoupling which is under the assumption that the sensor system is a linear system, another is the nonlinear decoupling which is under the assumption that the sensor system is a nonlinear system. The paper also analyzes and compares several commonly used decoupling algorithms of six-axis force/torque sensor from the aspects of decoupling effects and the accuracy of measurement, thus providing some academic bases and references for the further research of decoupling algorithm. Besides, taking the appropriate and effective decoupling algorithm can improve the measuring accuracy of the sensor to the largest extent, and meet the requirements for sensors reaching high-level, precise and sophisticated performances. Finally, the decoupling algorithms for six-axis force/torque sensor are summarized and its research direction can be foretold.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Binbin Han AU - Yingjun Li AU - Guicong Wang PY - 2016/11 DA - 2016/11 TI - Research of current studying status and developing trend of decoupling algorithm for six-axis force/torque sensor BT - 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/aest-16.2016.85 DO - https://doi.org/10.2991/aest-16.2016.85 ID - Han2016/11 ER -