2019 International Conference on Robotics and Automation (ICRA) 2019
DOI: 10.1109/icra.2019.8794382
|View full text |Cite
|
Sign up to set email alerts
|

Model Based In Situ Calibration with Temperature compensation of 6 axis Force Torque Sensors

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
12
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
4
2

Relationship

1
5

Authors

Journals

citations
Cited by 10 publications
(12 citation statements)
references
References 9 publications
0
12
0
Order By: Relevance
“…It was proven that adding the temperature led to a further increase in performance. Mixing types of datasets gave better results [14]. The in situ offset estimation type with temperature was shown to be better, followed closely by the centralized offset removal with or without temperature, using the same λ value.…”
Section: Previous Resultsmentioning
confidence: 83%
See 4 more Smart Citations
“…It was proven that adding the temperature led to a further increase in performance. Mixing types of datasets gave better results [14]. The in situ offset estimation type with temperature was shown to be better, followed closely by the centralized offset removal with or without temperature, using the same λ value.…”
Section: Previous Resultsmentioning
confidence: 83%
“…Experiments were performed on the floating base robot iCub. reliability of force torque sensors [14]. By extending its benefits and showcasing the improvement of floating base robots performance with this method, we aim to encourage the use of this sensor in these types of platforms in more effective ways.The most common phenomena used in FT sensors to measure forces is the change in resistance of silicon due to strain [15].…”
mentioning
confidence: 99%
See 3 more Smart Citations