Computing a Task-Dependent Grasp Metric Using Second Order Cone Programs
Amin Fakhari, Aditya Patankar, Jiayin Xie, and Nilanjan Chakraborty

TL;DR
This paper introduces a convex optimization-based grasp metric that evaluates a grasp's ability to generate desired motions by considering environmental contacts, external forces, and practical contact constraints, enhancing grasp analysis in manipulation tasks.
Contribution
The paper presents a novel SOCP formulation for grasp evaluation that accounts for environmental contacts and practical force constraints, improving upon existing methods.
Findings
Efficient computation of grasp quality using convex optimization.
Inclusion of environmental contacts in grasp analysis.
Ability to evaluate grasps for complex manipulation paths.
Abstract
Evaluating a grasp generated by a set of hand-object contact locations is a key component of many grasp planning algorithms. In this paper, we present a novel second order cone program (SOCP) based optimization formulation for evaluating a grasps' ability to apply wrenches to generate a linear motion along a given direction and/or an angular motion about the given direction. Our quality measure can be computed efficiently, since the SOCP is a convex optimization problem, which can be solved optimally with interior point methods. A key feature of our approach is that we can consider the effect of contact wrenches from any contact of the object with the environment. This is different from the extant literature where only the effect of finger-object contacts is considered. Exploiting the environmental contact is useful in many manipulation scenarios either to enhance the dexterity of…
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Taxonomy
TopicsRobot Manipulation and Learning · Robotic Path Planning Algorithms · Robotic Mechanisms and Dynamics
