Grasp planning under uncertainty

The planning of dexterous grasps for multifingered robot hands operating in uncertain environments is covered. A sensor-based approach to the planning of a reach path prior to grasping is first described. An on-line, joint space finger path planning algorithm for the enclose phase of grasping was then developed. The algorithm minimizes the impact momentum of the hand. It uses a Preshape Jacobian matrix to map task-level hand preshape requirements into kinematic constraints. A master slave scheme avoids inter-finger collisions and reduces the dimensionality of the planning problem

Constructing minimum deflection fixture arrangements using frame invariant norms

This paper describes a fixture planning method that minimizes object deflection under external loads. The method takes into account the natural compliance of the contacting bodies and applies to two-dimensional and three-dimensional quasirigid bodies. The fixturing method is based on a quality measure that characterizes the deflection of a fixtured object in response to unit magnitude wrenches. The object deflection measure is defined in terms of frame-invariant rigid body velocity and wrench norms and is therefore frame invariant. The object deflection measure is applied to the planning of optimal fixture arrangements of polygonal objects. We describe minimum-deflection fixturing algorithms for these objects, and make qualitative observations on the optimal arrangements generated by the algorithms. Concrete examples illustrate the minimum deflection fixturing method. Note to Practitioners-During fixturing, a workpiece needs to not only be stable against external perturbations, but must also stay within a specified tolerance in response to machining or assembly forces. This paper describes a fixture planning approach that minimizes object deflection under applied work loads. The paper describes how to take local material deformation effects into account, using a generic quasirigid contact model. Practical algorithms that compute the optimal fixturing arrangements of polygonal workpieces are described and examples are then presented

A stiffness-based quality measure for compliant grasps and fixtures

This paper presents a systematic approach to quantifying the effectiveness of compliant grasps and fixtures of an object. The approach is physically motivated and applies to the grasping of two- and three-dimensional objects by any number of fingers. The approach is based on a characterization of the frame-invariant features of a grasp or fixture stiffness matrix. In particular, we define a set of frame-invariant characteristic stiffness parameters, and provide physical and geometric interpretation for these parameters. Using a physically meaningful scheme to make the rotational and translational stiffness parameters comparable, we define a frame-invariant quality measure, which we call the stiffness quality measure. An example of a frictional grasp illustrates the effectiveness of the quality measure. We then consider the optimal grasping of frictionless polygonal objects by three and four fingers. Such frictionless grasps are useful in high-load fixturing applications, and their relative simplicity allows an efficient computation of the globally optimal finger arrangement. We compute the optimal finger arrangement in several examples, and use these examples to discuss properties that characterize the stiffness quality measure

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

Bio-Inspired Motion Strategies for a Bimanual Manipulation Task

Steffen JF, Elbrechter C, Haschke R, Ritter H. Bio-Inspired Motion Strategies for a Bimanual Manipulation Task. In: International Conference on Humanoid Robots (Humanoids). 2010

An Approach to Simultaneous Control of Trajectory and Interaction Forces in Dual-Arm Configurations

Multiple arm systems, multifingered grippers, and walking vehicles all have two common features. In each case, more than one actively coordinated articulation interacts with a passive object, thus forming one or more closed chains. For example, when two arms grasp an object simultaneously, the arms together with the object and the ground (base) form a closed chain. This induces kinematic and dynamic constraints and the resulting equations of motion are extremely nonlinear and coupled. Furthermore, the number of actuators exceeds the kinematic mobility of the chain in a typical case, which results in an underdetermined system of equations. An approach to control such constrained dynamic systems is described in this short paper. The basic philosophy is to utilize a minimal set of inputs to control the trajectory and the surplus inputs to control the constraint or interaction forces and moments in the closed chain. A dynamic control model is derived for the closed chain that is suitable for designing a controller, in which the trajectory as well as the interaction forces and moments are explicitly controlled. Nonlinear feedback techniques derived from differential geometry are then applied to linearize and decouple the nonlinear model. In this paper, these ideas are illustrated through a planar example in which two arms are used for cooperative manipulation. Results from a simulation are used to illustrate the efficacy of the method

Multiple cooperating manipulators: The case of kinematically redundant arms

Existing work concerning two or more manipulators simultaneously grasping and transferring a common load is continued and extended. Specifically considered is the case of one or more arms being kinematically redundant. Some existing results in the modeling and control of single redundant arms and multiple manipulators are reviewed. The cooperating situation is modeled in terms of a set of coordinates representing object motion and internal object squeezing. Nominal trajectories in these coordinates are produced via actuator load distribution algorithms introduced previously. A controller is developed to track these desired object trajectories while making use of the kinematic redundancy to additionally aid the cooperation and coordination of the system. It is shown how the existence of kinematic redundancy within the system may be used to enhance the degree of cooperation achievable

HEAP: A Sensory Driven Distributed Manipulation System

We address the problems of locating, grasping, and removing one or more unknown objects from a given area. In order to accomplish the task we use HEAP, a system of coordinating the motions of the hand and arm. HEAP also includes a laser range finer, mounted at the end of a PUMA 560, allowing the system to obtain multiple views of the workspace. We obtain volumetric information of the objects we locate by fitting superquadric surfaces on the raw range data. The volumetric information is used to ascertain the best hand configuration to enclose and constrain the object stably. The Penn Hand used to grasp the object, is fitted with 14 tactile sensors to determine the contact area and the normal components of the grasping forces. In addition the hand is used as a sensor to avoid any undesired collisions. The objective in grasping the objects is not to impart arbitrary forces on the object, but instead to be able to grasp a variety of objects using a simple grasping scheme assisted with a volumetric description and force and touch sensing