This paper reviews our ongoing efforts on designing a real-time vision system. The system consists of a real-time feature extractor and a relaxation network. The filter system is capable of performing multiple 2D non-separable filters, multi-resolution decomposition, and steerable transform. The relaxation network is capable of performing various relaxation, diffusion and minimization operations. The paper shows several vision tasks which can be implemented effectively on the vision system.

A single-link flexible manipulator with a rotary actuator at one end and a mass at the other is modeled using the Lagrangian method coupled with an assumed modes vibration model. A SIMO state space model is developed by linearizing the equations of motion and simplified by neglecting natural damping. Laplace domain pole-zero plots between torque input and tip position show nonminimum phase behavior. Nonminimum phase behavior causes difficulty for both conventional and artificial neural network (ANN) inverse-model control. The most promising ANN method for the control of flexible manipulators does not appear to converge to a solution when the system is lightly damped. To overcome this limitation, a modified cost function is proposed. Simulations show that the ANN is able to converge to a solution even in the case of no damping. The modified approach fails, however, for beams exceeding some critical length measure. Identification of the critical length and proposals for extending the result are discussed.

Article GT-EP: a novel high-performance real-time architecture Share on Authors: Wei Siong Tan Georgia Institute of Technology Georgia Institute of TechnologyView Profile , H. Russ Georgia Institute of Technology Georgia Institute of TechnologyView Profile , Cecil O. Alford Georgia Institute of Technology Georgia Institute of TechnologyView Profile Authors Info & Claims ISCA '91: Proceedings of the 18th annual international symposium on Computer architectureApril 1991 Pages 13–21https://doi.org/10.1145/115952.115955Online:01 April 1991Publication History 0citation329DownloadsMetricsTotal Citations0Total Downloads329Last 12 Months3Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Computing manipulator joint velocities and accelerations, given the end-effector Cartesian rates (velocities and accelerations), is complicated by the singular positions the manipulator can assume along a trajectory. At such configurations the Jacobi matrix that relates Cartesian end-effector rates to joint rates cannot be inverted. Geometric approaches in solving for joint rates yield expressions that are indeterminate at such configurations. It is shown that exact solutions for the joint rates can be obtained in most singularity situations if the system of differential kinematic relations is properly partitioned. A solution methodology is developed and illustrated by an example.>

A hybrid closed-loop system consists of a combination of continuous and discrete elements. Such systems are common in hybrid computer simulation or digital implementation of continuous controllers. The signal conversion process introduces errors into the system when compared with an equivalent system based on continuous variables. These errors, called sampling errors, are a function of several parameters within the digital part of the system. A model for these errors that can be used to estimate the effects that a particular hybrid implementation will have on the system response is developed in this work. An example is given to illustrate the application and accuracy of the equations.