Quantitative Steinitz's theorems with applications to multifingered grasping
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
Detection and Evaluation of Grasping Positions for Autonomous Agents
CW '05 Proceedings of the 2005 International Conference on Cyberworlds
Data-Driven Grasp Synthesis Using Shape Matching and Task-Based Pruning
IEEE Transactions on Visualization and Computer Graphics
Improving grasp quality evaluation
Robotics and Autonomous Systems
A method for grasp evaluation based on disturbance force rejection
IEEE Transactions on Robotics
A 3D shape segmentation approach for robot grasping by parts
Robotics and Autonomous Systems
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This paper focuses on the problem of grasp stability and grasp quality analysis. An elegant way to evaluate the stability of a grasp is to model its wrench space. However, classical grasp quality measures suffer from several disadvantages, the main drawback being that they are not task related. Indeed, constructive approaches for approximating the wrench space including also task information have been rarely considered. This work presents an effective method for task-oriented grasp quality evaluation based on a novel grasp quality measure. We address the general case of multifingered grasps with point contacts with friction. The proposed approach is based on the concept of programming by demonstration and interactive teaching, wherein an expert user provides in a teaching phase a set of exemplar grasps appropriate for the task. Following this phase, a representation of task-related grasps is built. During task planning and execution, a grasp could be either submitted interactively for evaluation by a non-expert user or synthesized by an automatic planning system. Grasp quality is then assessed based on the proposed measure, which takes into account grasp stability along with its suitability for the task. To enable real-time evaluation of grasps, a fast algorithm for computing an approximation of the quality measure is also proposed. Finally, a local grasp optimization technique is described which can amend uncertainties arising in supplied grasps by non-expert users or assist in planning more valuable grasps in the neighborhood of candidate ones. The paper reports experiments performed in virtual reality with both an anthropomorphic virtual hand and a three-fingered robot hand. These experiments suggest the effectiveness and task relevance of the proposed grasp quality measure.