Searching force-closure optimal grasps of articulated 2D objects with n links

This paper proposes a method that finds a locally optimal grasp of an articulated 2D object with n links considering frictionless contacts. The surface of each link of the object is represented by a finite set of points, thus it may have any shape. The proposed approach finds, first, an initial force-closure grasp and from it starts an iterative search of a local optimum grasp. The quality measure considered in this work is the largest perturbation wrench that a grasp can resist with independence of the direction of the perturbation. The approach has been implemented and some illustrative examples are included in the article.Postprint (published version

Frictionless grasp with 7 fingers on discretized 3D objects

This paper presents an algorithm to plain locally frictionless grasp on 3D objects. The objects can be of any arbitrary shape, since the surface is discretized in a cloud of points. The planning algorithm finds an initial force-closure grasp that is iteratively improved through an oriented search procedure. The grasp quality is measured with the “largest ball” criterion, and a force-closure test based on geometric considerations is used. The efficiency of the algorithm is illustrated through numerical example

Sampling-Based Methods for Factored Task and Motion Planning

This paper presents a general-purpose formulation of a large class of discrete-time planning problems, with hybrid state and control-spaces, as factored transition systems. Factoring allows state transitions to be described as the intersection of several constraints each affecting a subset of the state and control variables. Robotic manipulation problems with many movable objects involve constraints that only affect several variables at a time and therefore exhibit large amounts of factoring. We develop a theoretical framework for solving factored transition systems with sampling-based algorithms. The framework characterizes conditions on the submanifold in which solutions lie, leading to a characterization of robust feasibility that incorporates dimensionality-reducing constraints. It then connects those conditions to corresponding conditional samplers that can be composed to produce values on this submanifold. We present two domain-independent, probabilistically complete planning algorithms that take, as input, a set of conditional samplers. We demonstrate the empirical efficiency of these algorithms on a set of challenging task and motion planning problems involving picking, placing, and pushing

Independent contact regions for discretized 3D objects with frictionless contacts

This paper deals with the problem of determining independent contact regions on a 3D object boundary such that a seven finger frictionless grasp with a contact point in each region assures a force-closure grasp on the object, independently of the exact position of the contact points. These regions provide robustness in front of finger positioning errors in grasp and fixturing applications. The object’s structure is discretized in a cloud of points, so the procedure is applicable to objects of any arbitrary shape. The procedure finds an initial form-closure grasp that is iteratively improved through an oriented search procedure: once a locally optimum grasp has been reached, the independent contact regions are computed. The procedure has been implemented, and application examples are included in the paper

Determination of seven frictionless fixturing points searching the object surface with a homogeneous deterministic distribution

The paper deals whit the problem of finding a form-closure fixturing of objects modeled whit triangular meshes and considering as quality measure the maximum wrench that the object can resist in any direction. Although a triangular mesh is a polyhedral representation of the object, the number of faces is too large to allow a practical application of existing approaches for polyhedral objects, and therefore some search procedure have to be applied. In the proposed approach the search of contact points is done looking for points directly on the object boundary instead of on the wrench space. In this way, all the object surface is homogeneously considered, while the quality is evaluated in the wrench space. The procedure iteratively looks, using heuristic criteria, for sets of points that improve the quality. The procedure was implemented and some application examples are included in the paper to illustrate the performanc

Computation of independent contact regions for grasping 3-D objects

Precision grasp synthesis has received a lot of attention in past few last years. However, real mechanical hands can hardly assure that the fingers will precisely touch the object at the computed contact points. The concept of independent contact regions (ICRs) was introduced to provide robustness to finger positioning errors during an object grasping: A finger contact anywhere inside each of these regions assures a force-closure grasp, despite the exact contact position. This paper presents an efficient algorithm to compute ICRs with any number of frictionless or frictional contacts on the surface of any 3-D object. The proposed approach generates the independent regions by growing them around the contact points of a given starting grasp. A two-phase approach is provided to find a locally optimal force-closure grasp that serves as the starting grasp, considering as grasp quality measure the largest perturbation wrench that the grasp can resist, independently of the perturbation direction. The proposed method can also be applied to compute ICRs when several contacts are fixed beforehand. The approach has been implemented, and application examples are included to illustrate its performance.Peer Reviewe

PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning

Many planning applications involve complex relationships defined on high-dimensional, continuous variables. For example, robotic manipulation requires planning with kinematic, collision, visibility, and motion constraints involving robot configurations, object poses, and robot trajectories. These constraints typically require specialized procedures to sample satisfying values. We extend PDDL to support a generic, declarative specification for these procedures that treats their implementation as black boxes. We provide domain-independent algorithms that reduce PDDLStream problems to a sequence of finite PDDL problems. We also introduce an algorithm that dynamically balances exploring new candidate plans and exploiting existing ones. This enables the algorithm to greedily search the space of parameter bindings to more quickly solve tightly-constrained problems as well as locally optimize to produce low-cost solutions. We evaluate our algorithms on three simulated robotic planning domains as well as several real-world robotic tasks.Comment: International Conference on Automated Planning and Scheduling (ICAPS) 202

Grasp planning in discrete domain.

by Lam Miu-Ling.Thesis (M.Phil.)--Chinese University of Hong Kong, 2002.Includes bibliographical references (leaves 64-67).Abstracts in English and Chinese.Chapter Chapter 1. --- Introduction --- p.1Chapter Chapter 2. --- Mathematical Preliminaries and Problem Definition --- p.6Chapter 2.1 --- Grasp Synthesis in Discrete DomainChapter 2.2 --- AssumptionsChapter 2.3 --- Frictionless Form-Closure GraspChapter 2.4 --- Frictional Form-Closure GraspChapter 2.5 --- Problem DefinitionChapter Chapter 3. --- A Qualitative Test Algorithm and a Local Search Algorithm --- p.18Chapter 3.1 --- A Qualitative Test AlgorithmChapter 3.2 --- A Local Search AlgorithmChapter 3.3 --- Grasp Planning under Kinematic ConstraintsChapter Chapter 4. --- A Divide-and-Conquer Technique --- p.29Chapter 4.1. --- Determining a Separating HyperplaneChapter 4.2. --- Divide-and-Conquer in Frictionless CaseChapter 4.3. --- Divide-and-Conquer in Frictional CaseChapter Chapter 5. --- Implementation and Examples --- p.40Chapter 6.1. --- Examples of Frictionless GraspsChapter 6.2. --- Examples of Frictional GraspsChapter 6.3. --- Examples of Grasps under Kinematic ConstraintsChapter Chapter 6. --- Conclusions --- p.62Bibliography --- p.6