The Lego Mindstorms Robotics Invention System lets you design and program real robots that do what you want them to. By using artificial neural networks, you can build intelligent robots that can learn and show emergent behavior. This article describes the backpropagation algorithm, a basic neural network, and its implementation on a Lego Roverbot with Java.
Sometimes what I do as job can have some major personal pluses (I get to play with robots some of the time), one of these has been the opportunity to introduce people to social robots, and recently I have been lucky enough to managed to do this four times- twice to my own computing students, but also to groups of primary school children in two events (see below).
Apart from it's what I enjoyed doing; the social robots we are starting to see are great, but there is so much more that could be done. Who is going to develop this - possibly one of these children? Why not? It has taken nearly 40 years to get from R2D2 on the screen to some of the social robots we are seeing launched now, in another 40 years we might have something as bright as R2D2 (R2D2 was always brighter than C3PO). Why wouldn't one or more of these bright children or one of the students I teach, be the ones to contribute to this? They have the enthusiasm, with the changes in the National Curriculum in the UK they are developing some of the skills and asking the questions. Look at the work that work being done by Pi Foundation, the CamJam EduKit 3 robot kit (http://camjam.me/?page_id=1035) and especially products such as the OhBot (see bottom of the post for details of this robot) as just as a few examples of how this is being developed.
Simulation is a valuable tool to improve the energy efficiency of machines and it is now being used to analyze and optimize soft robotic systems to increase their utility, as described in an article published in Soft Robotics
I only had about 2 1/2 hours at BETT 2017 due to external time pressures so to say I didn't yet a chance for a good (or even a bad) look around is an understatement; so I am not reviewing the show just a few notes on what I did manage to see.
Self-driving cars could account for 21 million new vehicles sold every year by 2035. Over the next decade alone such vehicles—and vehicles with assisted-driving technology —could deliver $1 trillion in societal and consume
The proliferation of soft robotics research worldwide has brought substantial achievements in terms of principles, models, technologies, techniques, and prototypes of soft robots. Such achievements are reviewed here in terms of the abilities that they provide robots that were not possible before. An analysis of the evolution of this field shows how, after a few pioneering works in the years 2009 to 2012, breakthrough results were obtained by taking seminal technological and scientific challenges related to soft robotics from actuation and sensing to modeling and control. Further progress in soft robotics research has produced achievements that are important in terms of robot abilities—that is, from the viewpoint of what robots can do today thanks to the soft robotics approach. Abilities such as squeezing, stretching, climbing, growing, and morphing would not be possible with an approach based only on rigid links. The challenge ahead for soft robotics is to further develop the abilities for robots to grow, evolve, self-heal, develop, and biodegrade, which are the ways that robots can adapt their morphology to the environment.
Think your office is too cluttered for a robot to deal with? New research from KTH Royal Institute of Technology in Stockholm shows how robots can autonomously 'learn' their way around a dynamic human environment.
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