scholarly journals RTHybrid: A Standardized and Open-Source Real-Time Software Model Library for Experimental Neuroscience

2019 ◽  
Vol 13 ◽  
Author(s):  
Rodrigo Amaducci ◽  
Manuel Reyes-Sanchez ◽  
Irene Elices ◽  
Francisco B. Rodriguez ◽  
Pablo Varona
Keyword(s):  
Open Source ◽  
Real Time ◽  
Model Library ◽  
Software Model

scholarly journals RTHybrid: a standardized and open-source real-time software model library for experimental neuroscience

2018 ◽  
Author(s):  
Rodrigo Amaducci ◽  
Manuel Reyes-Sanchez ◽  
Irene Elices ◽  
Francisco B. Rodriguez ◽  
Pablo Varona
Keyword(s):  
Open Source ◽  
Real Time ◽  
Open Source Software ◽  
Closed Loop ◽  
Temporal Precision ◽  
Model Library ◽  
Software Model ◽  
Synapse Model ◽  
Living Neurons ◽  
Partially Observable

ABSTRACTClosed-loop technologies provide novel ways of online observation, control and bidirectional interaction with the nervous system, which help to study complex non-linear and partially observable neural dynamics. These protocols are often difficult to implement due to the temporal precision required when interacting with biological components, which in many cases can only be achieved using real-time technology. In this paper we introduce RTHybrid (www.github.com/GNB-UAM/RTHybrid), a free and open-source software that includes a neuron and synapse model library to build hybrid circuits with living neurons in a wide variety of experimental contexts. In an effort to encourage the standardization of real-time software technology in neuroscience research, we compared different open-source real-time operating system patches, RTAI, Xenomai 3 and Preempt-RT, according to their performance and usability. RTHybrid has been developed to run over Linux operating systems supporting both Xenomai 3 and Preempt-RT real-time patches, and thus allowing an easy implementation in any laboratory. We report a set of validation tests and latency benchmarks for the construction of hybrid circuits using this library. With this work we want to promote the dissemination of standardized, user-friendly and open-source software tools developed for open- and closed-loop experimental neuroscience.

Open source real-time operating systems for plasma control at FTU

2004 ◽  
Vol 51 (3) ◽  
pp. 476-481 ◽  
Author(s):  
C. Centioli ◽  
F. Iannone ◽  
G. Mazza ◽  
M. Panella ◽  
L. Pangione ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Operating Systems ◽  
Plasma Control

Open-Source Real-Time Robot Operation and Control System for Highly Dynamic, Modular Machines

2013 ◽  
Author(s):  
Andrew Peekema ◽  
Daniel Renjewski ◽  
Jonathan Hurst
Keyword(s):  
Control System ◽  
Open Source ◽  
Real Time ◽  
High Frequency ◽  
Performance Test ◽  
Frequency Control ◽  
Human Robot Interaction ◽  
Sensors And Actuators ◽  
Key Innovation ◽  
Hard Real Time

The control system of a highly dynamic robot requires the ability to respond quickly to changes in the robot’s state. This type of system is needed in varying fields such as dynamic locomotion, multicopter control, and human-robot interaction. Robots in these fields require software and hardware capable of hard real-time, high frequency control. In addition, the application outlined in this paper requires modular components, remote guidance, and mobile control. The described system integrates a computer on the robot for running a control algorithm, a bus for communicating with microcontrollers connected to sensors and actuators, and a remote user interface for interacting with the robot. Current commercial solutions can be expensive, and open source solutions are often time consuming. The key innovation described in this paper is the building of a control system from existing — mostly open source — components that can provide realtime, high frequency control of the robot. This paper covers the development of such a control system based on ROS, OROCOS, and EtherCAT, its implementation on a dynamic bipedal robot, and system performance test results.

A mobile sensor package for real-time greenhouse monitoring using open-source hardware

2019 ◽  
Author(s):  
Lars Larson ◽  
Elad Levintal ◽  
Jose Manuel Lopez Alcala ◽  
Dr. Lloyd Nackley ◽  
Dr. John Selker ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Mobile Sensor ◽  
Sensor Package ◽  
Open Source Hardware

scholarly journals Real Time Object Detection Canbe Embedded on Low Powered Devices

2019 ◽  
Author(s):  
Jimut Bahan Pal
Keyword(s):  
Neural Networks ◽  
Object Detection ◽  
Open Source ◽  
Real Time ◽  
Detection System ◽  
Computing Power ◽  
Convolution Neural Networks ◽  
Real Challenge ◽  
New Algorithms

It has been a real challenge for computers with low computing power and memory to detect objects in real time. After the invention of Convolution Neural Networks (CNN) it is easy for computers to detect images and recognize them. There are several technologies and models which can detect objects in real time, but most of them require high end technologies in terms of GPUs and TPUs. Though, recently many new algorithms and models have been proposed, which runs on low resources. In this paper we studied MobileNets to detect objects using webcam to successfully build a real time objectdetection system. We observed the pre trained model of the famous MS COCO dataset to achieve our purpose. Moreover, we applied Google’s open source TensorFlow as our back end. This real time object detection system may help in future to solve various complex vision problems.

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