Abstract not found

In this paper, we survey the work in robotic grasping related areas that has been done over the last two decades, with a bias toward the development of the theoretical framework and analytical results in this area. In addition we assess the state of the art in this area and outline some of the important open problems.

This paper describes our current research into nonprehensile palm manipulation. The term “palm ” refers to the use of the entire device surface during manipulation, as opposed to use of the fingertips alone.

The hierarchical generalized Voronoi graph (HGVG) is a roadmap that can serve as a basis for sensor based robot motion planning. A key feature of the HGVG is its incremental construction procedure that uses only line of sight distance information. This work describes basic properties of the HGVG and the procedure for its incremental construction using local range sensors. Simulations and experiments verify this approach. 1 Introduction Sensor based motion planning incorporates sensor information, reflecting the current state of the environment, into a robot's planning process, as opposed to classical planning, which assumes full knowledge of the world's geometry prior to planning. Sensor based planning is important for realistic deployment of robots because: (1) the robot often has no a priori knowledge of the world; (2) the robot may have only a coarse knowledge of the world because of limited computer memory; (3) the world model is bound to contain inaccuracies which can be overcom...

Research in robotic grasping has flourished in the last 25 years. A recent survey by Bicchi [1] covered over 140 papers, and many more than that have been published. Stemming from our desire to implement some of the work in grasp analysis for particular hand designs, we created an interactive grasping simulator that can import a wide variety of hand and object models and can evaluate the grasps formed by these hands. This system, dubbed “GraspIt!,” has since expanded in scope to the point where we feel it could serve as a useful tool for other researchers in the field. To that end, we are making the system publicly available (GraspIt! is available for download for a variety of platforms from

In this paper, an attempt at summarizing the evolution and the state-of-the-art in the field of robot hands is made. In such exposition, a critical evaluation of what in the author's view are the leading ideas and emerging trends, is privileged with respect to exhaustiveness of citations. The survey is focused mainly on three types of functional requirements a machine hand can be assigned in an artificial system, namely, manipulative dexterity, grasp robustness, and human operability. A basic distinction is made between hands designed for mimicking the human anatomy and physiology, and hands designed to meet restricted, practical requirements. In the latter domain, arguments are presented in favor of a "minimalistic" attitude in the design of hands for practical applications, i.e., use the least number of actuators, the simplest set of sensors, etc., for a given task. To achieve this rather obvious engineering goal is a challenge to our community. The paper illustrates some of the ...

Geometric uncertainty is unavoidable when programming robots for physical applications. We propose a stochastic framework for manipulation planning where plans are ranked on the basis of expected cost. That is, we express the desirability of states and actions with a cost function and describe uncertainty with probability distributions. We illustrate the approach with a new design for a programmable parts feeder, a mechanism that orients two-dimensional parts using a sequence of open-loop mechanical motions. We present a planning algorithm that accepts an n-sided polygonal part as input and, in time O(n²), generates a stochastically optimal plan for orienting the part.

Fixturing is a fundamental problem in mechanical assembly. Usually, two and a half dimensional objects can be fixtured in many different ways using a fixture vice, especially if pegs of different radii are available. We present an algorithm which enumerates all force closure fixture vice configurations and corresponding object poses. Automatic fixture design algorithms are essential for planning because optimal fixturing selection for multiple operations requires examining all of the valid configurations. The algorithm runs in O(A) time, where A is the number of configurations which simultaneously contact the object. 1 Introduction The task of immobilizing a workpiece via mechanical devices, commonly called fixturing or workholding, is an essential problem in manufacturing. Machining fixtures must handle very large forces (20KN), whereas assembly fixtures handle smaller forces (50N). Fixture apparatus design is more a craft than a science. Without geometric analysis, a fixturing exp...

Three important problems in the study of grasping and manipulation by multifingered robotic hands are: (a) Given a grasp characterized by a set of contact points and the associated contact models, determine if the grasp has force closure; (b) If the grasp does not have force closure, determine if the ngers are able to apply a specified resultant wrench on the object; and (c) Compute "optimal" contact forces if the answer to problem (b) is affirmative. In this paper, based on an early result by Buss, Hashimoto and Moore, which transforms the nonlinear friction cone constraints into positive definiteness of certain symmetric matrices, we further cast the friction cone constraints into linear matrix inequalities (LMIs) and formulate all three of the problems stated above as a set of convex optimization problems involving LMIs. The latter problems have been extensively studied in optimization and control community and highly efficient algorithms with polynomial time complexity are now available for their solutions. We perform simulation studies to show the simplicity and efficiency of the LMI formulation to the three problems.

We have created a unique tool for grasp simulation, visualization, and analysis that allows a user to create and analyze grasps of a given 3D object model with a given articulated hand model. The grasps can be performed either automatically, where the system closes the fingers around the object at preset velocities, or manually through direct manipulation of the joints. As collisions occur between the links of the fingers and the object, the system locates the contacts and analyzes the evolving grasp on the fly. Each time the grasp changes, the system updates two numeric measures of quality and recomputes 3D projections of the grasp wrench space which are useful when visualizing a grasp's capabilities. We provide examples of the system being used with four different articulated robotic hand models, each grasping different object models. We feel the system is very useful for hand designers who prototype different hand models in simulation and determine how design decisions affect a hand...