Corpus ID: 6853822

Dexterous Grasping via Eigengrasps : A Low-dimensional Approach to a High-complexity Problem

@inproceedings{Ciocarlie2007DexterousGV,
  title={Dexterous Grasping via Eigengrasps : A Low-dimensional Approach to a High-complexity Problem},
  author={M. Ciocarlie and Corey Goldfeder and P. Allen},
  year={2007}
}
In this paper, we build upon recent advances in neuroscience research which have shown that control of the human hand during grasping is dominated by movement in a configuration space of highly reduced dimensionality. We extend this concept to robotic hands and show how a similar dimensionality reduction can be defined for a number of different hand models. This framework can be used to derive optimization algorithms that simplify the task of finding stable grasps even for highly complex hand… Expand

Figures and Tables from this paper

On-Line Interactive Dexterous Grasping
TLDR
A system that combines human input and automatic grasp planning for controlling an artificial hand, with applications in the area of hand neuroprosthetics, is described. Expand
Biomimetic grasp planning for cortical control of a robotic hand
TLDR
A grasp planning system designed to augment the cortical control of a prosthetic arm and hand with the ability to combine online user input and autonomous planning to enable the execution of stable grasping tasks is outlined. Expand
Towards Postural Synergies for Caging Grasps
Postural synergies have in recent years been successfully used as a low-dimensional representation for the control of robotic hands and in particular for the synthesis of force-closed grasps. ThisExpand
A Geometric Approach for Grasping Unknown Objects With Multifingered Hands
TLDR
This article proposes a method for grasping unknown objects from cluttered scenes using a noisy point cloud as an input using a shape complementarity metric and proposes an optimization-based refinement of the hand poses and finger configurations to achieve a power grasp of the target object. Expand
Quasi-Static Analysis of Synergistically Underactuated Robotic Hands in Grasping and Manipulation Tasks
TLDR
Numerical results are presented for a power grasp example, the analysis of which is initially performed for the case of fully-actuated hand, and later verifying, after the introduction of a synergistic underactuation, which capacities of the system are lost, and which other are still present. Expand
Postural Hand Synergies during Environmental Constraint Exploitation
TLDR
The hypothesis that humans' ability to intuitively exploit the shape of an object and environmental constraints to achieve stable grasps and perform dexterous manipulations can be described in terms of a synergistic behavior in the generation of hand postures is formulated, i.e., using a reduced set of commonly used kinematic patterns. Expand
Simply Grasping Simple Shapes: Commanding a Humanoid Hand with a Shape-Based Synergy
TLDR
This method can be applied to any position-controlled humanoid hand to decrease the number of commanded DoF based on simple, measurable inputs in order to grasp commonly shaped objects and has the potential to vastly expand the library of objects the robot can manipulate. Expand
Toward Dexterous Manipulation With Augmented Adaptive Synergies: The Pisa/IIT SoftHand 2
TLDR
A novel robotic hand, the Pisa/IIT SoftHand 2.0, which demonstrates that by opportunely combining only two DoAs with hand softness, a large variety of grasping and manipulation tasks can be performed, only relying on the intelligence embodied in the mechanism. Expand
Grasp compliance regulation in synergistically controlled robotic hands with VSA
TLDR
The approach is based on the iterative exploration of the equilibrium manifold of the system and the quasi-static analysis of the governing equations and can cope with large commanded variations of the grasp stiffness with respect to an initial configuration. Expand
Humanlike, task-specific reaching and grasping with redundant arms and low-complexity hands
TLDR
The final scheme provides anthropomorphic robot motion, task-specific robot arm configurations and hand grasping postures, optimized fingertips placement on the object surface (that results to robust grasps) and guaranteed convergence to the desired goals. Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 16 REFERENCES
Nullspace composition of control laws for grasping
TLDR
Three control laws are combined by projecting the actions of subordinate control laws into other control law nullspaces and the resulting composite controller finds grasps that are more robust than the component primitives in isolation. Expand
Manipulation gaits: sequences of grasp control tasks
  • Robert Platt, A. Fagg, R. Grupen
  • Engineering, Computer Science
  • IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004
  • 2004
TLDR
It is shown that dexterous manipulation can be viewed as a task that is accomplished in the context of a wrench closure constraint, and hypothesize this approach can generalize to any task that must be accomplished while maintaining a set of constraints. Expand
Automatic grasp planning using shape primitives
TLDR
This paper aims to simplify automatic grasp planning for robotic hands by modeling an object as a set of shape primitives, such as spheres, cylinders, cones and boxes, to generate aSet of grasp starting positions and pregrasp shapes that can then be tested on the object model. Expand
On grasp choice, grasp models, and the design of hands for manufacturing tasks
  • M. Cutkosky
  • Engineering, Computer Science
  • IEEE Trans. Robotics Autom.
  • 1989
TLDR
Comparisons of the grasp taxonomy, the expert system, and grasp-quality measures derived from the analytic models reveal that the analytic measures are useful for describing grasps in manufacturing tasks despite the limitations in the models. Expand
Graspit! A versatile simulator for robotic grasping
TLDR
The different types of world elements and the general robot definition are discussed and the robot library is presented, and the grip analysis and visualization method were presented. Expand
A biocybernetic method to learn hand grasping posture
TLDR
A biocybernetic method to learn hand grasping posture definition with few knowledge about the task is proposed and simulation results show good learning of grasping posture determination of various object types, with different numbers of fingers involved and different contact configurations. Expand
Robotic Grasping of Novel Objects
TLDR
This work presents a learning algorithm that neither requires, nor tries to build, a 3-d model of the object, instead it predicts, directly as a function of the images, a point at which to grasp the object. Expand
Planning optimal grasps
  • C. Ferrari, J. Canny
  • Engineering, Computer Science
  • Proceedings 1992 IEEE International Conference on Robotics and Automation
  • 1992
TLDR
Two general optimality criteria that consider the total finger force and the maximum finger force are introduced and discussed and the geometric interpretation of the two criteria leads to an efficient planning algorithm. Expand
Postural Hand Synergies for Tool Use
TLDR
The results suggest that the control of hand posture involves a few postural synergies, regulating the general shape of the hand, coupled with a finer control mechanism providing for small, subtle adjustments. Expand
The Robonaut hand: a dexterous robot hand for space
  • C. Lovchik, M. Diftler
  • Engineering, Computer Science
  • Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C)
  • 1999
TLDR
A highly anthropomorphic human scale robot hand designed for space based operations is presented and it approximates very well the kinematics and required strength of an astronaut's hand when operating through a pressurized space suit glove. Expand
...
1
2
...