Title
Finger-Shaped GelForce: Sensor for Measuring Surface Traction Fields for Robotic Hand
Abstract
It is believed that the use of haptic sensors to measure the magnitude, direction, and distribution of a force will enable a robotic hand to perform dexterous operations. Therefore, we develop a new type of finger-shaped haptic sensor using GelForce technology. GelForce is a vision-based sensor that can be used to measure the distribution of force vectors, or surface traction fields. The simple structure of the GelForce enables us to develop a compact finger-shaped GelForce for the robotic hand. GelForce that is developed on the basis of an elastic theory can be used to calculate surface traction fields using a conversion equation. However, this conversion equation cannot be analytically solved when the elastic body of the sensor has a complicated shape such as the shape of a finger. Therefore, we propose an observational method and construct a prototype of the finger-shaped GelForce. By using this prototype, we evaluate the basic performance of the finger-shaped GelForce. Then, we conduct a field test by performing grasping operations using a robotic hand. The results of this test show that using the observational method, the finger-shaped GelForce can be successfully used in a robotic hand.
Year
DOI
Venue
2010
10.1109/TOH.2009.47
Haptics, IEEE Transactions
Keywords
Field
DocType
gelforce technology,robotic hand,vision-based sensor,conversion equation,measuring surface traction fields,finger-shaped haptic sensor,finger-shaped gelforce,compact finger-shaped gelforce,observational method,complicated shape,haptic sensor,prototypes,humanoid robots,testing,shape,image sensors,force sensor
Force sensor,Computer vision,Robotic hand,Image sensor,Observational method,Computer science,Simulation,Control engineering,Traction (engineering),Artificial intelligence,Haptic technology,Humanoid robot
Journal
Volume
Issue
ISSN
3
1
1939-1412
Citations 
PageRank 
References 
26
2.06
6
Authors
4
Name
Order
Citations
PageRank
Katsunari Sato116521.32
Kazuto Kamiyama213315.81
Naoki Kawakami347565.36
Susumu Tachi41294221.20