JOURNAL ARTICLE

Dynamic Nonprehensile Manipulation: Controllability, Planning, and Experiments

Kevin LynchMatthew T. Mason

Year: 1999 Journal:   The International Journal of Robotics Research Vol: 18 (1)Pages: 64-92   Publisher: SAGE Publishing

Abstract

We are interested in using low-degree-of-freedom robots to perform complex tasks by nonprehensile manipulation (manipulation without aformorforce-closure grasp). By notgrasping, the robot can usegravitational, centrifugal, and Coriolisforces as virtual motors to control more degrees of freedom of the part. The part s extra motionfreedoms are exhibited as rolling, slipping, and free flight. This paper describes controllability, motion planning, and implementation ofplanar dynamic nonprehensile manipukltion. We show that almost any planar object is controllable by point contact, and the controlling robot requires only twvo degrees of freedom (a point translating in the plane). We then focus on a one-joint manipulator (with a two-dimensional state space), and show that even this simplest of robots, by using slipping and rolling, can control a planar object to a fulldimensional subset of its six-dimensional statespace. We have developed a one-jointrobotto perform a variety of dynamic tasks, including snatching an object ftom a table, rolling an object on the surface of the arm, and throwing and catching. Nonlinear optimization is used to plan robot trajectories that achieve the desired object motion via coupling forces though the nonprehensile contact.

Keywords:
Controllability GRASP Robot Control theory (sociology) Slipping Computer science Object (grammar) Degrees of freedom (physics and chemistry) Point (geometry) Control engineering Engineering Artificial intelligence Mathematics Control (management) Mechanical engineering Physics

Metrics

233
Cited By
14.64
FWCI (Field Weighted Citation Impact)
111
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Robot Manipulation and Learning
Physical Sciences →  Engineering →  Control and Systems Engineering
Robotic Path Planning Algorithms
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotic Mechanisms and Dynamics
Physical Sciences →  Engineering →  Control and Systems Engineering

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