Title
Tactile-Based In-Hand Object Pose Estimation.
Abstract
This paper presents a method to estimate the pose of an object inside a robotic hand by exploiting contact and joint position information. Once an initial visual estimation is provided, a Bootstrap Particle Filter is used to evaluate multiple hypothesis for the object pose. The function used to score the hypothesis considers feasibility and physical meaning of the contacts between the object and the hand. The method provides a good estimation of in-hand pose for different 3D objects.
Year
DOI
Venue
2017
10.1007/978-3-319-70836-2_59
ROBOT 2017: THIRD IBERIAN ROBOTICS CONFERENCE, VOL 2
Keywords
Field
DocType
Robotic grasping,Object pose estimation,Tactile sensing
Visual estimation,Computer vision,Robotic hand,Computer science,Particle filter,Pose,Artificial intelligence,Bootstrapping (electronics)
Conference
Volume
ISSN
Citations 
694
2194-5357
0
PageRank 
References 
Authors
0.34
9
3
Name
Order
Citations
PageRank
David Álvarez1124.35
Máximo A. Roa237327.42
L. Moreno317622.59