The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Robot-assisted therapy has been researched for more than a decade and has been dominated by the seal shaped robot Paro. It is however unclear unto what extent the development of Paro has been based upon requirements that are mentioned by care professionals. In this pilot study we interviewed two groups of healthcare professionals: one that has been using Paro and one that has not been using Paro....
We present a Cellular Neural Network (CNN) model in which cells are constituted by autonomous robots implementing some standard templates. The system can be interpreted as a multi-core processor acting on the robot environment, being each robot one of the cores. This is a particular case of robot swarm which benefits from the simplicity of the CNN template implementation.
In this paper we present a complete study on the balance between high performance image processing and low power consumption without using expensive components. Our proposal consists in implementing a Discrete Time Cellular Neural Network (DT-CNN) on a low power Actel IGLOO nano Field Programmable Gate Array (FPGA). This is a definitive step further from previous work to obtain an intelligent camera...
This paper introduces two applications of Discrete Time Cellular Non-Linear Networks (DTCNN) in a robot guiding avoiding obstacles algorithm and prove the feasibility of both applications: a high data rate one, using a CMOS camera, and small data rate one, using ultrasonic sensors. The key value of DTCNNs is the locally connections and the parallelism in processing. These characteristics permit a...
This paper presents an implementation of a DTCNN, programmed entirely in LEGO Mindstorms NXT robot to, together with perceptron, guide a robot avoiding obstacles. The map will be processed DTCNN obtained from ultrasonic and infrared sensors. The main objective of this implementation is to demonstrate the feasibility of implementing these and other applications of the CNN with Minstorm LEGO NXT.
This paper presents the application of an 8-bit Field Programmable Gate Array (FPGA) implementation of a Discrete Time Cellular Neural Network (DTCNN) suitable for small image gray-scale pre-processing (simple operations with high computational burden). It uses Split & Shift techniques to have a 12 ?? 12 grid. Reduced grid is necessary because of windowing process is added to process bigger images...
This paper presents an 8-bit FPGA implementation of a discrete time cellular neural network (DTCNN) suitable for small image gray-scale pre-processing (simple operations with high computational burden). It uses Split&Shift techniques to have a 31 times 31 grid that processes more than 2500 images per second. As this work evolves from a previous binary DTCNN implementation, results are compared...
The so-called split&shift (S&S) methodology has previously been introduced as an effective area saving technique for hardware implementation of cellular non-linear networks. This work provides the first experimental proof of such a methodology through a circuit implementation over an FPGA platform. Results of area, processing time and functionality of different instances of the S&S methodology...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.