Manipulation without prehension is a natural way of handling objects for both humansand machines. Nonprehensile operations are appropriate when complete constraint over the object to be manipulated is either undesirableor impractical, but some control overthe object is desired over its entire trajectory, in orderto bring the object reliably to a desired final state. Research to date has explored only a small portion of this class. We are interested in controlling the shape of the constraint surfaces so that constraint and externalforcesnaturally attract the systemto the desired state, even if the object momentarily loses stability during the motion. We present a preliminary analysisof the nonprehensile orientation of planar objects by two low friction palms joined at a central hinge. These palms support an object in a gravitational field, without grasping or gripping. We determine connected regions of stable states of the object, and give a method of planning part orientation based on ...

A process monitor for robotic assembly based on Hidden Markov Models (HMMs) is presented. The HMM process monitor is based on the dynamic force/torque signals arising from interaction between the workpiece and the environment. The HMMs represent a stochastic, knowledge-based system where the models are trained off-line with the Baum-Welch re-estimation algorithm. The assembly task is modeled as a discrete event dynamic system, where a discrete event is defined as a change in contact state between the workpiece and the environment. Our method 1) allows for dynamic motions of the workpiece, 2) accounts for sensor noise and friction and 3) exploits the fact that the amount of force information is large when there is a sudden change of discrete state in robotic assembly. After the HMMs have been trained, we use them on-line in a 2D experimental setup to recognise discrete events as they occur. Successful event recognition with an accuracy as high as 97% was achieved in 0.5-0.6 seconds with...

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A stability cell is a subset of the configuration space (C-space) of a set of actively controlled rigid bodies (e.g., a whole-arm manipulator) in contact with a passive body (e.g., a manipulated object) in which the contact state is guaranteed to be stable under the influence of Coulomb friction and external forces. A first-order stability cell is a subset of a stability cell with the following two properties: first, the state of contact uniquely determines the rate of change of the object's configuration given the rate of change of the manipulator's configuration; and second, the contact state cannot be altered by any infinitesimal variation in the generalized applied force. First-order This research was supported in part by the National Science Foundation, grant no. IRI-9304734, the Texas Advanced Research Program, grant no. 999903-078, the Texas Advanced Technology Program, grant no. 999903-095, and NASA Johnson Space Center through the Universities' Space Automation and Robotics...

The most secure type of grasp of a frictionless woorkpiece is the form-closure grasp. However, task constraints may make achieving form-closure impossible or undesirable. In this case, one needs to employ a force-closure 1 grasp. In this paper, we study the subclass of force-closure grasps known as second-order stable grasps, which typically have a small number of contacts. We derive conditions for second-order stability and represent second-order stability cells as conjunctions of equations and inequalities in the configuration variables of the system. These cells are the subsets of the system's configuration space for which the frictionless workpiece is second-order stable. We also determine the minimum and maximum numbers of contacts necessary for second-order stability. Our results are applied to a simple planar whole-arm manipulation system to generate one of its second-order stability cells. 1 Introduction Consider a multi-arm robotic system or hand manipulating a frictionles...

We address the global motion planning aspects of dextrous manipulation by a multi-fingered robotic hand. The specific task we address is: starting from a given initial grasp of a 3D object O, find feasible quasi-static trajectories (rolling/sliding motions and forces) for the fingertips to move O to a desired final configuration. We call this the re-configuration problem. Our planner is based on a two-level algorithm combining a graph search on the configuration space of the object and a local planner that solves for instantaneous quasi-static motions of the entire manipulation system. The planner is used for simulating several complex re-configuration tasks for polyhedral and smooth objects demonstrating the practicality and the promise of our approach.

The contribution of this paper is the expansion of the range of possibilities in the analysis, planning, and control of contact tasks. The successful execution of any contact task fundamentally requires the application of wrenches (forces and moments) consistent with the task. We develop an algorithm for computing the entire set of external wrenches consistent with achieving a given augmented contact mode (e.g., sliding at contact 1, rolling at contact 2, and approaching potential contact 3) for one fixed and one moving part in the plane.

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This paper outlines geometric and algorithmic issues common to various types of nonprehensile manipulation and gives some results for planar dynamic manipulation. 1 Overview Nonprehensile manipulation is manipulation without a form- or force-closure grasp. Examples include pushing, throwing, juggling, tapping, batting, and rolling (Mason [24]; Higuchi [11]; Buhler and Koditschek [6]; Erdmann [8]; Huang et al. [12]; Zumel and Erdmann [40]; Aiyama et al. [1]; Trinkle and Zeng [37]). In each of these examples, the robot takes advantage of the natural task dynamics to help control the motion of the part. Nonprehensile manipulation occupies the majority of the manipulation spectrum, comprising everything between situations where the robot exerts complete control to situations where the natural dynamics exert complete control. During a baseball throw, the ball is at first held firmly in the hand, then is allowed to roll off the fingers, and finally follows a free-flight trajectory determined by gravity and air resistance. The nonprehensile manipulation problem is to arrange the rolling motion on the fingers such that the release state will allow the ball to reach the goal state

The companion paper [2] derives an algorithm that determines the external wrenches consistent with constraints on the contact interactions between two rigid planar bodies. In this paper, we show how this algorithm may be used to create sensorless plans that guarantee that a workpiece is correctly inserted into a fixture. Our method explicitly removes all wrenches consistent with undesirable contact modes, and therefore avoids the frictional indeterminacy problem.