Gregory P. Starr

Swing-Free Transport of Suspended Objects With a Path-Controlled Robot Manipulator

Objects which cannot be directly grasped by the end effector of a robot manipulator and must be carried by a hook or similar device are susceptible to swinging during transport. For a simply suspended object, it is possible to use a path-controlled manipulator to achieve a swing-free motion. The trajectory consists of an initial acceleration to an intermediate velocity, then a secondary acceleration to final velocity. An experimental demonstration of the method is presented.

Grasp synthesis of polygonal objects using a three-fingered robot hand

Grasping an object with a multifingered robot hand requires complete constraint of its motion by contacts. Complete con straint of an object can also be described using force equilib rium. If any external force on the object can be balanced by applicable contact forces, a stable grasp has been achieved. A force closure grasp is such a grasp. This article presents a simple and efficient algorithm to find an optimum force clo sure grasp of a planar polygon using a three fingered robot hand. The optimum grasp is defined as a grasp that has the minimum value of a heuristic function. The heuristic function is formulated from the consideration of the possible uncertainties inherent in implementation. Even though a planar force clo sure grasp can be obtained using only two friction contacts, we consider only grasps where all three friction contacts explicitly participate. To find the optimum grasp, all feasible combina tions of edges and/or vertices are identified first. An edges and/or vertices combination is feasible when a stable grasp is attainable by an appropriate selection of three contacts on them. Then, using computational geometry, a single grasp is constructed on each feasible combination. Finally, the grasps obtained are compared using the heuristic quality measure. A test of our algorithm on several different polygons shows that the resulting grasp is realistic and is obtained fast enough for real-time use.

Modeling and control of the stanford/JPL hand

Improved dexterity is an area of current research in robotics. At Sandia National Laboratories and the University of New Mexico we are pursuing research in this area with the aid of a Stanford/JPL hand from Salisbury Robotics. In this paper we present some of the issues raised in studying the characteristics and control of a single finger of the dexterous hand. The issues we present are dynamic modeling, friction based hysteresis, and identification of the finger system. We also discuss our present method for sensing and control.

An Automated Method to Calibrate Industrial Robots Using a Virtual Closed Kinematic Chain

This paper describes an industrial robot calibration algorithm called the virtual closed kinematic chain method. Current robot kinematic calibration methods use measurements of position and orientation of the end effector. The accuracy of these measurements is limited by the resolution of the measuring equipment. In the proposed method, a laser pointer tool, attached to the robots end effector, aims at a constant but unknown location on a fixed object, effectively creating a virtual 7 DOFs closed kinematic chain. As a result, small variations in position and orientation of the end effector are magnified on the distant object. Hence, the resolution of observations is improved, increasing the accuracy of joint angle measurements that are required to calibrate the robot. The method is verified using both simulation and real experiments. It is also shown in simulation that the method can be automated by a feedback system that can be implemented in real time. The accuracy of the robot after using the proposed calibration procedure is measured by aiming at an arbitrary fixed point and measuring the mean and standard deviation of the radius of spread of the projected points. The mean and standard deviation of the radius of spread were improved from 5.64 and 1.89 mm to 1.05 and 0.587 mm, respectively.

Finger force computation for manipulation of an object by a multifingered robot hand

The authors present an efficient computational procedure to determine the finger force of a three-fingered robot hand in object manipulation. They first define initial grasping force as the force needed to hold a massless object. Then grasping force and contact normal during manipulation are determined from initial grasping force and initial contact normal by tracking the object displacement. Manipulation force, the finger force required to manipulate an object and to compensate for object weight, is computed by the generalized matrix inverse method. Optimal internal force, when necessary, is determined from the grasping force during manipulation without explicitly solving the optimization problem. The computational burden for determining finger force is less than that of previous methods.<<ETX>>

Rapid Swing-Free Transport of Nonlinear Payloads Using Dynamic Programming

Residual vibration suppression in freely suspended payload transports has been the focus of extensive work in the past. Many methods have been used to address this problem, including both open-loop motion planning and closed-loop control techniques. However, to be effective, most of these methods require linearization of the system and, in turn, have been restricted in their maneuver speeds. The inherent nonlinearity of suspended payload systems suggests the need for a more rigorous method, where the complete dynamic description can be retained throughout the optimization. Dynamic programming (DP) is such a method. This paper will outline the development of the DP algorithm for a discrete time system as well as its application to the rapid transport of a doubly suspended payload, a nonlinear system. The system consists of a long slender payload, suspended by a cable at each end. The two cables are each held by an independent robot manipulator. We will show that DP is effective at reducing residual oscillations for nonlinear systems, as demonstrated by both simulations and experimental validation. Residual oscillations were suppressed to less than 5% of their original magnitudes.

Grasp synthesis of polygonal objects

A simple and efficient algorithm is presented to find the best force closure grasp on a planar polygon with a three-fingered robot hand. In searching for the best grasp, force closure grasps on each feasible combination of edges and/or vertices are constructed using computational geometry. A heuristic function formulated from the consideration of uncertainty in grasping is used to evaluate the quality of each grasp. A test of the algorithm on several different polygons shows that the resulting grasp is realistic and fast enough for real-time use.<<ETX>>

Augmented Sliding Mode Control for Flexible Link Manipulators

A method of sliding mode control (SMC) is proposed for the control of flexible, nonlinear, and structural systems. The method departs from standard sliding mode control by dispensing with generalized accelerations during the control law design. Global, asymptotic stability of rigid body motion is maintained if knowledge on the bounds of the neglected terms exists. Furthermore, this method provides damping for the measured flexible body modes. This paper investigates an augmented SMC technique for slewing flexible manipulators. A conventional sliding surface uses a first order system including a combination of error and error rate terms. The augmented sliding surface includes an enhanced term that helps to reject flexible degrees-of-freedom. The algorithms are theoretically developed and experimentally tested on a slewing single flexible link robot. The test apparatus is instrumented with a strain gauge at the root and an accelerometer attached at the tip. A DC motor and encoder are used to servo the link from an initial position to a final position. A standard cubic polynomial is employed to generate the reference trajectories. The augmented SMC algorithm showed improved performance by reducing the flexible link tip oscillations.

Calibration of industrial robots by magnifying errors on a distant plane

This paper describes a robot calibration approach called the virtual closed kinematic chain (ViCKi) method. Traditionally, calibration requires the measurement of the position and orientation of the end effector, and measurement resolution limits the accuracy of the robot model. In ViCKi, we attach a laser to the end effector to create a virtual 7th link. The laser spot produced on a distant plane, the end of this virtual link, magnifies small changes at the end effector, resulting in a high resolution error measurement of the end effector. The accuracy of the robot after using the proposed calibration procedure is measured by aiming at an arbitrary fixed point and measuring the mean and standard deviation of the radius of spread of the projected points. The mean and standard deviation of the radius of spread were improved from 5.64 mm and 1.89 mm to 1.05 mm and 0.587 mm respectively. It is also shown in simulation that the method can be automated by a feedback system that can be implemented in real-time.

A framework for implementing cooperative motion on industrial controllers

The use of two or more robots jointly manipulating a common object, termed cooperative control, has many advantages in industrial applications. Much of the previous work on cooperative control, however, has emphasized capabilities, such as joint torque control, not generally present on industrial robots. This paper applies the concept of cooperative control to industrial robots by taking advantage of those capabilities that do exist on industrial robots. Specifically, a design approach that makes use of tool-based coordinate systems, trajectory generation, real-time modification, and distributed control of multiple robots is presented. These concepts are implemented on a system of two industrial robots using an adaptive fuzzy controller, and the results are discussed.