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interview by   -   November 26, 2016

wetlab

In this episode, Audrow Nash interviews Dieter Fox, Professor in the Department of Computer Science and Engineering at the University of Washington, about the 100/100 Computer Vision Tracking Challenge. This is a self-imposed challenge to understand 100% of the pixels in an image 100% of the time in video footage; this includes understanding semantic information. Such understanding would allow robots to assist humans more naturally in environments like a home kitchen, wet lab, or in disaster response. To accomplish this challenge, Fox discusses challenges which include modeling, tracking, and detecting articulated objects.

by   -   November 16, 2016

bc-robot-interface

Research and development of robotic assistive technologies has gained tremendous momentum in the last decade due to several factors such as the maturity level reached by several technologies, the advances in robotics and AI and the fact that more than 700 million of persons have some kind of disability or handicap. For many people with mobility impairments, essential and simple tasks, such as dressing or feeding, require the assistance of dedicated people. Thus, the use of devices providing independent mobility can have a large impact on their quality of life.

by and   -   November 8, 2016

swarming-botsWhat can swarm roboticists learn from policy makers, systems biologists and physicists, and vice versa? It is already widely recognised that Robotics is an inherently interdisciplinary field and that designing even a single robot might require input from multiple domains. In Swarm Robotics, interactions between robots add further layers of complexity. Indeed, the ‘complex’ nature of robot swarm systems demands approaches going beyond reductionist scientific models or traditional engineering design methods. Like many other emerging technologies, such as synthetic biology and socio-technical systems engineering, robot swarms can be notoriously difficult to predict due to their non-linearity, interconnectivity, hidden heterogeneity and ’emergence‘. Yet it is also this ‘complexity’ that swarm roboticists seek to exploit in order to give intelligent, robust, adaptive behaviours.

But what does it mean to describe systems as complex? How do these complex systems differ from the more easily understood ‘modular’ systems that we are familiar with? Vocabulary in this area is often dangerously inconsistent. For example, the terms ’emergence’, ‘complex’, and ‘complicated’ are used differently by different disciplines, and often differently even within the same discipline. This makes it very difficult to understand whether people are really talking about the same thing, and whether the systems being described are different in superficial or profound ways. On the one hand, failing to identify the underlying similarities between different systems (whether modular or complex) results in missed opportunities for sharing knowledge, best practices and methods. On the other hand, failing to identify the underlying differences between different systems results in practices and methods being misapplied. More broadly, many of today’s real-world problems require engineers, designers and policy-makers across all domains to think in terms of complex systems.
triple-pageTo address problems with translating between disciplines, Chih-Chun Chen and Nathan Crilly at the University of Cambridge have produced ‘A primer on the design and science of complex systems’. This introduces complex systems constructs by building them up from basic concepts, and contrasting them with more familiar constructs that are associated with modularity. For example, ’emergence’ can be understood with respect to a breakdown in how a system’s functions are mapped to the structures that perform those functions. Abstract diagrams that are independent of any particular domain are used to represent the constructs that are discussed. These are illustrated with worked examples that make the explanations accessible for those who have no experience with ‘complexity’. The primer is intended to provide both an introduction to complex systems constructs for those new to the topics discussed, and also a basis for cross-domain translations for researchers and practitioners wishing to engage with other fields when addressing the systems problems they are working on.

Being able to communicate unambiguously across disciplines and application areas would greatly expand the space of solutions available to all domains in solving problems currently deemed to be too ‘complex’. As a mature complex systems engineering discipline which is by its nature interdisciplinary, Swarm Robotics will no doubt have much to contribute to – and take from – this endeavour.

If you liked this article, you may also want to read these other articles on swarm robotics:

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Frame of the tutoring experience of the student with low motivation and high competence. Reproduced with permission from the parents of the children. Courtesy of Dr Imbernon Cuadrado
Frame of the tutoring experience of the student with low motivation and high competence. Reproduced with permission from the parents of the children. Courtesy of Dr Imbernon Cuadrado

By: Ian Salter

The use of robotic tutors in primary school classrooms is one step closer according to research recently published in the open access journal Frontiers in Computational Neuroscience.

Dr Imbernòn Cuadrado and his co-workers at the Department of Artificial Intelligence in Madrid have developed an integrated computational architecture (ARTIE) for use with software applications in schools.

interview by   -   October 31, 2016

xemo_jpg

In this episode, Abate De Mey interviews Jeff Sprenger, founder of the startup Xemory in Vermont, USA. At Xemory they are developing a robot simulation game called Xemo, where players learn to animate virtual robots.

Complex motion at each joint is broken down into its more fundamental components, called degrees of freedom. Players are faced with the challenge of controlling the several degrees of freedom to recreate lifelike motions such as crawling, walking, jumping, and even dancing. These challenges are similar to the ones faced by roboticists trying to develop lifelike, robust and balanced motions for legged robots.

Sprenger discusses the unique ways different age groups and genders interact with the software. Through incorporating feedback from the students, Sprenger adds new activities and challenges to keep students engaged and challenged, improving their understanding of robot control.

by   -   October 7, 2016

raheeb

Raheeb Muzaffar, an information technology specialist, has developed an application-layer framework that improves the transmission of videos between moving drones and mobile devices located at ground level. His work within the Interactive and Cognitive Environments (ICE) doctoral programme will be completed soon. Raheeb explains what makes this technology innovative and talks about his plans for the future in a conversation with Romy Mueller.

interview by   -   October 3, 2016

rss


In this episode, Audrow Nash interviews several researchers presenting their work at the Robotics Science and Systems (RSS) 2016 conference in Ann Arbor, Michigan.

interview by   -   August 6, 2016

Black-rhino-Yoki-WC

In this episode, Audrow Nash interviews Fredrik Gustafsson, Professor in Sensor Informatics at Department of Electrical Engineering in Linköping University, about an initiative to reduce poaching in a rhino sanctuary in Ngulia, Kenya. Gustafsson discusses how he first became involved in this project, how he has worked with the rangers to develop solutions, and the future of this work.

interview by   -   July 23, 2016

pbo

In this episode, Audrow Nash interviews Emo Todorov, Director of Movement Control Laboratory at the University of Washington, about a physics-based optimization method for controlling robots. Todorov describes how his physics-based method can be used to solve problems and discusses results in simulation and on hardware.

interview by   -   June 25, 2016

icra2016

This is the second of two episodes where Audrow Nash interviews several companies at the International Conference for Robotics and Automation (ICRA). ICRA is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work. The 2016 conference was May 16-21 in Stockholm, Sweden.

by   -   June 1, 2016
Code review of a C++ program with an error found.
Code review of a C++ program with an error found.

I have been part of many software teams where we desired to do code reviews. In most of those cases the code reviews did not take place, or were pointless and a waste of time. So the question is: how do you effectively conduct peer reviews in order to improve the quality of your systems?

I found this book, Peer Reviews in Software: A Practical Guide by Karl E. Wiegers. This book was recommended to me, and having “practical guide” in the title caught my attention —  I have reviewed other books that claimed practical, but were not. Hopefully this book will help provide me (and you) with tools for conducting valuable code reviews.

interview by   -   May 1, 2015

In this episode, Audrow Nash interviews Todd Hylton, Senior Vice President at Brain Corporation, about neuromorphic computers. They discuss the robotics development board bStem, which approximates a neuromorphic computer, as well as the eyeRover: a small balancing robot that demonstrates how the bStem can be used in mobile robots.

by   -   April 15, 2015

coding

I have often thought about what the proper software methodology should be for the various robots that I build. My thoughts have evolved over time as I have seen these tool work. While I do not have any formal software engineering training, these are the common principles that I have seen, heard, read, etc. that I believe in (at 2am while I write this).

interview by   -   March 20, 2015

emotion_robots2

In this episode, Audrow Nash interviews Christina Brester, from the Siberian State Aerospace University, about her research on a method to identify emotional state from speech. This method performs speech analysis with a self-adaptive, multi-objective, genetic algorithm for feature selection and uses a neural network to classify those features. In this interview, we’ll discuss exactly what that means, as well as the implications and future of this research.

by   -   March 4, 2014

Drone-Failsafe-Algorithm

UPDATE 04/03/2014:

In this video update, we show that a quadrocopter can be safely piloted by hand after a motor fails, without the aid of a motion capture system. This follows our previous video, where we demonstrated how a complete propeller failure can be automatically detected, and that a quadrocopter can still maintain stable flight despite the complete loss of a propeller. 





Venture capital in robotics
August 23, 2013


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