Authors:
Venkataramani Rakesh
1
;
Utkarsh Sarma
2
;
Murugan S
1
;
Venugopal Srinivasan
1
and
Thondiyath Asokan
2
Affiliations:
1
Indira Gandhi Centre for Atomic Research, India
;
2
Indian Institute of Technology Madras, India
Keyword(s):
Grasping, Robot Hand, Synthesis, Particle Swarm Optimisation (PSO), Grasp Quality.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Engineering Applications
;
Evolutionary Computing
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Robot Design, Development and Control
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Soft Computing
;
Telerobotics and Teleoperation
Abstract:
Automated grasp planning for robotic hands is a complex problem when compared with the ease with which human hands grasp objects. Research in robotic grasp synthesis attempts to find novel ways in which a stable grasp can be achieved reliably. In this work, we present a grasping methodology that achieves optimized force closure grasps on 3D irregular objects. 3D objects in the form of polygonal meshes are parameterized to 2D shapes in order to reduce the search space by constraining robotic hands finger tips to be in contact with the objects surface. We use a Particle Swarm Optimization (PSO) based framework to optimize an initial grasp. The scheme has been validated on test-case 3D objects represented with surface tessellation for a 5-fingered DLR robotic hand.