In this episode, Audrow Nash interviews Federico Parietti, a PhD candidate at the Massachusetts Institute of Technology, about his research on supernumerary robotic limbs that can be used in manufacturing and for rehabilitative purposes, among other uses.
The videos below demonstrate how supernumerary limbs can be used to assist in tasks. This research was done in the same lab that Federico works in.
Federico Parietti is currently a PhD candidate at the Massachusetts Institute of Technology, where his research focuses on the design and control of wearable robots and man-machine interfaces. Previously, Parietti was a Research Associate and Visiting Scholar at Carnegie Mellon University and an International Student at ETH Zurich, in Switzerland.
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.
As Senior Vice President of Brain Corporation, Dr. Todd Hylton leads the development of business and technical strategies within the company. A scientist and co founder of a small semi-conductor equipment manufacturer, Hylton brings 25 years of experience in the semiconductor, optical communications, data storage and defense industries alongside a broad technical entrepreneurial background in research and development, small business, marketing and government programs.
In this podcast, Ron Vanderkley speaks to Donal Holland of Harvard University about his team’s work on the Soft Robotics Toolkit.
Soft Robotics is a class of elastically soft, versatile, and biologically inspired machines represents an exciting and highly interdisciplinary paradigm in engineering that could revolutionize the role of robotics in healthcare, field exploration, and cooperative human assistance.
The Soft Robotics Toolkit is a collection of shared resources to support the design, fabrication, modelling, characterization, and control of soft robotic devices. The toolkit was developed as part of educational research being undertaken in the Harvard Biodesign Lab. The ultimate aim of the toolkit is to advance the field of soft robotics by allowing designers and researchers to build upon each other’s work. The web site contains the open source fluidic control board, detailed design for wide range soft robotic components (including actuators and sensors).
The growing popularity of site is now bringing in hobbyist and makers alike. The Soft Robotics Toolkit team has announce two competitions intended to reward students, researchers, makers, and designers of all levels for their contributions to the field of soft robotics.
Donal Holland is a visiting Lecturer in Engineering Sciences at Harvard School of Engineering and Applied Sciences Demographic info Ireland | Mechanical or Industrial Engineering. He was a passed PhD Student at Trinity College Dublin, Visiting Fellow at Harvard School of Engineering and Applied Sciences, Research Assistant at Treocht Ltd.
In this episode, Sabine Hauert interviews main stakeholders in European Robotics at the European Robotics Forum in Vienna.
Cécile Huet, Deputy Head of the Robotics Unit at the European Commission, gives us an overview of the new wave of robotics projects funded under Horizon2020, with a focus on robots that can help people and drive application. She also tells us about the tools available to fund the full pipeline from research projects to hubs of excellence in robotics.
Uwe Haass, previous Secretary General of the non-profit EURobotics, looks at the Association’s work to develop a roadmap for European Robotics and their efforts to bring industry and academia closer. The recommendations from EURobotics are then used to help drive the funding strategy of the European Commission.
Together, the European Commission and EURobotics form a public-private partnership named SPARC which invests over €2.8 billion in robotics. For more information, check the figure below.
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.
Christina Brester completed her bachelor’s (2012) and master’s degree (2014) at the Siberian State Aerospace University (SibSAU) in Krasnoyarsk, Russia. Her master’s thesis was on Speech-based Emotion Recognition.
Currently, Brester is a PhD student in Computer Science and Engineering at SibSAU. Her research interests include evolutionary computation, neuro-evolutionary algorithms, machine learning, and speech analysis.