Paper Info
Title
Human-inspired robotic grasping of flat objects.
Abstract
In this paper, we propose a human-inspired framework for grasping domestic flat objects placed on planar support surfaces. In particular, three grasp strategies are proposed which aim to pinch small flat objects from different scenes. The framework uses representations of the robotic hand, the support surface and the target object which encapsulate rough information for the scene. Furthermore, the strategies exploit the environmental constraint of the support surface by establishing compliant contact with it, which leads to increased robustness against object geometry uncertainties as well as pose estimation errors possibly introduced by the perception system. This is inspired by how humans perform relative grasping tasks with object pose and geometry uncertainties by using compliant contact with the support surfaces. Finally, the strategy selection is determined by a decision making procedure which uses the current scene representation.
Year
DOI
Venue
2018
10.1016/j.robot.2018.07.005
Robotics and Autonomous Systems
Keywords
Field
DocType
Human-inspired grasping,Environmental constraints,Flat objects
Computer vision,Perception system,GRASP,Robotic hand,Computer science,Support surface,Robustness (computer science),Pose,Exploit,Planar,Artificial intelligence
Journal
Volume
ISSN
Citations 
108
0921-8890
3
PageRank 
References 
Authors
0.46
14
2
Name
Order
Citations
PageRank
Iason Sarantopoulos132.49
Zoe Doulgeri233247.11