GRASP is a Greedy Randomised Adaptive Sampling Procedure that has been proposed to estimate parameters of self-exciting autoregressive threshold models (SETARs) with multivariate thresholds. We show that the GRASP procedure can often lead to an incorrect number of thresholds when estimating SETARs. Two simple modifications of the original GRASP procedure are suggested to overcome this problem. ...

Grasp densities are designed to be learned empirically. In principle, a robot attemps to grasp the object a large number of times using a wide variety of object-relative gripper poses. Each successful grasp constitutes a data point drawn from the underlying grasp density (1). In practice, for reasons of efficiency, attempted grasps should be chosen in an informed manner [1]. For resampling and ...

In this talk a greedy randomized adaptive search procedure (GRASP) is presented for computing approximate solutions to the NP-hard three-index assignment problem (AP3). A FORTRAN implementation of this GRASP is tested on several problem instances of the AP3. A parallelization strategy that combines GRASP and path relinking is also proposed and tested for the problem. Computational results indic...

BACKGROUND The Graded Repetitive Arm Supplementary Program (GRASP) is a hand and arm exercise programme designed to increase the intensity of exercise achieved in inpatient stroke rehabilitation. GRASP was shown to be effective in a randomised controlled trial in 2009 and has since experienced unusually rapid uptake into clinical practice. The aim of this study was to conduct a formative evalua...

In this article, we study the problem of selecting a grasp pose on the surface of an object to be manipulated by considering three post-grasp objectives. These objectives include (i) kinematic manipulation capability [1], [2], (ii) torque effort [3] and (iii) impact force in case of collision [4] during post-grasp manipulative actions. In these works [1]–[4], the main assumption is that a manip...

Copyright is held by the author/owner. CHI 2011, May 7-12 2011, Vancouver, BC, Canada. ACM 978-1-4503-0268-5/11/05 Abstract The way we grasp an object depends on several factors, for example the intended goal or the hand's anatomy. Therefore, a grasp can convey meaningful information about its context. Inferring these factors from a grasp allows us to enhance interaction with tools and artifact...

This paper discusses the computerization of an existent tool called GRASP. It helps teachers to design an instructional system. Currently, GRASP has the form of a grid. Teachers complete it to first clarify their instructional problem and then to design an instructional system. This tool covers the analysis and design phases of the ADDIE (Analyze, Design, Develop, Implement and Evaluate) model....

A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimization. It is a multi-start or iterative process, in which each GRASP iteration consists of two phases, a construction phase, in which a feasible solution is produced, and a local search phase, in which a local optimum in the neighborhood of the constructed solution is sought. Since 1989, numerous p...