Embedded Implementation of a Real-Time Motion Estimation Method in Video Sequences

AbstractThis paper presents an embedded implementation of a hardware-efficient method for motion information extraction from a video signal. The high computing cost of gradient-based methods makes their implementation in compact devices for real-time applications challenging. We present our achievements in implementing a novel, simplified version of a gradient-based method, using an FPGA circuit-based system for on-line Sobel edge detection and edge displacement-based optical flow computation. The image data is acquired from a dedicated embedded camera transmitted to the reconfigurable platform. The design and implementation steps of the devised method are presented, followed by the description of the system's setup and measurement results. The yielded results are compared to similar implementations. These results lead to possibilities in using the developed system for the enhancement of indoor mobile robot localization

Web-Based Interfaces for Virtual C. elegans Neuron Model Definition, Network Configuration, Behavioral Experiment Definition and Experiment Results Visualization

The Si elegans platform targets the complete virtualization of the nematode Caenorhabditis elegans, and its environment. This paper presents a suite of unified web-based Graphical User Interfaces (GUIs) as the main user interaction point, and discusses their underlying technologies and methods. The user-friendly features of this tool suite enable users to graphically create neuron and network models, and behavioral experiments, without requiring knowledge of domain-specific computer-science tools. The framework furthermore allows the graphical visualization of all simulation results using a worm locomotion and neural activity viewer. Models, experiment definitions and results can be exported in a machine-readable format, thereby facilitating reproducible and cross-platform execution of in silico C. elegans experiments in other simulation environments. This is made possible by a novel XML-based behavioral experiment definition encoding format, a NeuroML XML-based model generation and network configuration description language, and their associated GUIs. User survey data confirms the platform usability and functionality, and provides insights into future directions for web-based simulation GUIs of C. elegans and other living organisms. The tool suite is available online to the scientific community and its source code has been made available

7th International Robotic Sailing Conference

An autonomous sailboat robot is a boat that only uses the wind on its sail as the propelling force, without remote control or human assistance to achieve its mission. Robotic sailing offers the potential of long range and long term autonomous wind propelled, solar or wave-powered carbon neutral devices. Robotic sailing devices could contribute to monitoring of environmental, ecological, meteorological, hydrographic and oceanographic data. These devices can also be used in traffic monitoring, border surveillance, security, assistance and rescue. The dependency on changing winds and sea conditions presents a considerable challenge for short and long term route and stability planning, collision avoidance and boat control. Building a robust and seaworthy sailing robot presents a truly complex and multi-disciplinary challenge for boat designers, naval architects, systems/electrical engineers and computer scientists. Over the last decade, several events such as Sailbot, World Robotic Sailing Championship and the International Robotic Sailing Conference (WRSC/IRSC) and Microtransat have sparked an explosion in the number of groups working on autonomous sailing robots. Many of the challenges in building truly autonomous sailing robots still remain unsolved. These proceedings present the work of researchers on current and future challenges in autonomous sailboat development, presented at the WRSC/IRSC 2014 in Galway, Ireland, 8th – 12th September 2014.

Xilinx FPGA implementation of a pixel processor for object detection applications

This paper describes an FPGA and distributed RAM architecture for an image pixel processor implementing primary elements of an object detection system. A comparison of the system performance with existing DSP processor-based alternatives is detailed. An implementation using the RC1000-PP FPGA-based development platform and Handel-C hardware programming language is outlined. A system architecture is proposed for an image pixel processor for elements of a machine vision based object detection systems