Bayesian grasping

A Bayesian approach to the problem of autonomous manipulation in the presence of state uncertainty is described. Uncertainty is modeled with a probability distribution on the state space. Each plan (sequence of actions) defines a mapping on the state space and hence a posterior probability distribution. An attempt is made to find a plan for optimizing expected performance. The Bayesian framework is applied to a grasping problem. A planar polygon whose initial orientation is described by a uniform distribution and a frictionless parallel-jaw gripper is assumed in order to plan automatically a sequence of open-loop squeezing operations to reduce orientational uncertainty and grasp the object. Although many different performance measures are possible depending on the application, the approach is illustrated by searching for plans that optimize the robot's expected throughput.<<ETX>>

[1]  Karl Johan Åström,et al.  Adaptive feedback control , 1987, Proc. IEEE.

[2]  Vladimir J. Lumelsky,et al.  Algorithmic and complexity issues of robot motion in an uncertain environment , 1987, J. Complex..

[3]  Gregory D. Hager,et al.  Active reduction of uncertainty in multisensor systems , 1988 .

[4]  H. Hanafusa,et al.  Stable Prehension by a Robot Hand with Elastic Fingers , 1977 .

[5]  Max Mintz,et al.  Sensor modeling and robust sensor data fusion , 1991 .

[6]  Balas K. Natarajan.  Some Paradigms for the Automated Design of Parts Feeders , 1989, Int. J. Robotics Res..

[7]  Russell H. Taylor,et al.  Automatic Synthesis of Fine-Motion Strategies for Robots , 1984 .

[8]  Hideo Hanafusa,et al.  Stable Prehension of Objects by the Robot Hand with Elastic Fingers , 1977 .

[9]  Matthew T. Mason,et al.  Automatic planning of fine motions: Correctness and completeness , 1984, ICRA.

[10]  Avinash C. Kak,et al.  Planning sensing strategies in a robot work cell with multi-sensor capabilities , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[11]  Stephen J. Buckley.  Planning and teaching compliant motion strategies , 1987 .

[12]  Matthew T. Mason,et al.  An exploration of sensorless manipulation , 1986, IEEE J. Robotics Autom..

[13]  Aristides A. G. Requicha,et al.  Toward a Theory of Geometric Tolerancing , 1983 .

[14]  Arthur C. Sanderson,et al.  Planning robotic manipulation strategies for workpieces that slide , 1988, IEEE J. Robotics Autom..

[15]  Peter C. Cheeseman,et al.  In Defense of Probability , 1985, IJCAI.

[16]  Russell H. Taylor,et al.  Sensor-based manipulation planning as a game with nature , 1988 .

[17]  Matthew T. Mason,et al.  Mechanics and Planning of Manipulator Pushing Operations , 1986 .

[18]  Randy C. Brost,et al.  Automatic Grasp Planning in the Presence of Uncertainty , 1988, Int. J. Robotics Res..

[19]  Peter Cheeseman,et al.  On the Representation and Estimation of Spatial Uncertainty , 1986 .

[20]  A. H. Redford,et al.  Statistical distributions of natural resting aspects of parts for automatic handling , 1977 .

[21]  Ruzena Bajcsy,et al.  Machine Systems for Exploration and Manipulation: A Conceptual Framework and Method of Evaluation , 1989 .

[22]  Rodney A. Brooks,et al.  Symbolic Error Analysis and Robot Planning , 1982 .