Paper Info
Title
Grasp recognition and mapping on humanoid robots
Abstract
In this paper, we present a system for vision-based grasp recognition, mapping and execution on a humanoid robot to provide an intuitive and natural communication channel between humans and humanoids. This channel enables a human user to teach a robot how to grasp an object. The system comprises three components: human upper body motion capture system which provides the approaching direction towards an object, hand pose estimation and grasp recognition system, which provides the grasp type performed by the human as well as a grasp mapping and execution system for grasp reproduction on a humanoid robot with five-fingered hands. All three components are real-time and markerless. Once an object is reached, the hand posture is estimated, including hand orientation and grasp type. For the execution on a robot, hand posture and approach movement are mapped and optimized according to the kinematic limitations of the robot. Experimental results are performed on the humanoid robot ARMAR-IIIb.
Year
DOI
Venue
2009
10.1109/ICHR.2009.5379538
Humanoids
Keywords
Field
DocType
humanoid robots,image motion analysis,pose estimation,robot vision,ARMAR-IIIb humanoid robot,grasp recognition system,hand pose estimation,human upper body motion capture system,natural communication channel,vision-based grasp recognition
Computer vision,Motion capture,GRASP,Kinematics,Computer science,Simulation,Image segmentation,Pose,Artificial intelligence,Robot,Robotics,Humanoid robot
Conference
ISBN
Citations 
PageRank 
978-1-4244-4588-2
7
0.56
References 
Authors
23
4
Name
Order
Citations
PageRank
Martin Do11288.24
javier romero299134.17
Kjellstrom, H.370.56
pedram azad441825.86