Towards a reactive grasping system for an industrial robot arm
- 20 January 2003
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
As robots are being increasingly called to operate out of well-structured environments, our contribution focuses in the grasp determination in unknown objects, vision being the exclusive mode of perception. Two strategies based on visual parameters extracted from 2D scenes are presented. The first one seeks the object's contour for a grasp that is optimal within a gravitational field, while the second one aims at locating all the grasps that meet certain contact stability criteria, ignoring the gravitational field assumption. Both strategies are complementary in the sense that they endow a robot with different manipulation skills in complex, non-structured scenarios, and can be easily integrated in the implementation of a reactive behavior for the robot.Keywords
This publication has 10 references indexed in Scilit:
- Learning to grasp using visual informationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- On computing two-finger force-closure grasps of curved 2D objectsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Vision-guided grasping of unknown objects for service robotsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Towards autonomous robotic servicing: Using an integrated hand-arm-eye system for manipulating unknown objectsRobotics and Autonomous Systems, 1999
- Planar Grasping Characterization Based on Curvature-Symmetry FusionApplied Intelligence, 1999
- An automatic transformation from bimodal to pseudo-binary imagesPublished by Springer Nature ,1997
- Applying vision guidance in robotic food handlingIEEE Robotics & Automation Magazine, 1996
- A Symmetry Theory of Planar GraspThe International Journal of Robotics Research, 1995
- Active Perception and Exploratory RoboticsPublished by Springer Nature ,1993
- Symmetry-curvature dualityComputer Vision, Graphics, and Image Processing, 1987