In this episode, Marwa ElDiwiny interview Peer Fisher, a Professor of Physical Chemistry at the University of Stuttgart and the Director of the Micro Nano and Molecular Systems Lab at the Max Planck Institute for Intelligent Systems.  Fischer discusses micro robots that has been designed to move inside of environments similar to the human body called, “micro swimmers.”  He talks about how they are fabricated, powered, and how they can move with light or “nano propellers.”  Fischer also discusses simulating human tissue and the future of micro and nano robots, including how they could be a replacement for certain surgeries.

Three projects have made the final cut and received funding for a ROBOTT-NET pilot and even further development assistance.

In this episode, Abate interviews Andrew Stein from Anki. At Anki they developed an engaging robot called Cozmo which packs sophisticated robotic software inside a lifelike, palm sized, robot. Cozmo recognizes people and objects around him and plays games with them. Cozmo is unique in that a large amount of development has been implemented to make his animations and behavior feel natural, in addition to focusing on classical robotic elements such as computer vision and object manipulation.

In this episode, Jack Rasiel interviews Vijay Kumar, Professor and Dean of Engineering at the University of Pennsylvania.  Kumar discusses the guiding ideas behind his research on micro unmanned aerial vehicles, gives his thoughts on the future of robotics in the lab and field, and speaks about setting realistic expectations for robotics technology.

A robotic doctor that can be controlled hundreds of kilometres away by a human counterpart is gearing up for action. Getting a check-up from a robot may sound like something from a sci-fi film, but scientists are closing in on this real-life scenario and have already tested a prototype.

In this episode, Audrow Nash interviews Sergey Levine, assistant professor at UC Berkeley, about deep learning on robotics. Levine explains what deep learning is and he discusses the challenges of using deep learning in robotics. Lastly, Levine speaks about his collaboration with Google and some of the surprising behavior that emerged from his deep learning approach (how the system grasps soft objects).

In addition to the main interview, Audrow interviewed Levine about his professional path. They spoke about what questions motivate him, why his PhD experience was different to what he had expected, the value of self-directed learning,  work-life balance, and what he wishes he’d known in graduate school.

By Eran Klein, University of Washington and Katherine Pratt, University of Washington

In the 1995 film “Batman Forever,” the Riddler used 3-D television to secretly access viewers’ most personal thoughts in his hunt for Batman’s true identity. By 2011, the metrics company Nielsen had acquired Neurofocus and had created a “consumer neuroscience” division that uses integrated conscious and unconscious data to track customer decision-making habits. What was once a nefarious scheme in a Hollywood blockbuster seems poised to become a reality.

MIT CSAIL approach allows robots to learn a wider range of tasks using some basic knowledge and a single demo.

What do you get when you put together wood and rope? Well according to Plymouth University’s Professor Guido Bugmann: a low-cost, open source, 2 meter tall robot! All buildable for under £2000. The Cheap Arm Project (CHAP) began as an MSc project aimed at developing an affordable mobile robot arm system that could be used by wheelchair users to access daily objects at inaccessible heights or weights (the extreme case being 2 litre bottle).

This comprehensive tutorial offers a step-by-step guide to using UgCS software to plan and fly UAV drone-survey missions.

For robots to do what we want, they need to understand us. Too often, this means having to meet them halfway: teaching them the intricacies of human language, for example, or giving them explicit commands for very specific tasks. But what if we could develop robots that were a more natural extension of us and that could actually do whatever we are thinking?

Felix Von Drigalski, of the Nara Institute of Science and Technology, introduces a versatile, open-source, two-finger gripper for textile manipulation that can sustain significant pushing loads in order to perform tucking tasks, using active perception.

In this episode, Abate De Mey interviews two speakers from the Agricultural track of the RoboUniverse 2016 conference in San Diego: Dan Harburg of Soft Robotics Inc. and Matthew Borzage of BioTac. Borzage and Harburg discuss their distinct approaches to advancing gripping technology in Agriculture. Borzage stresses the importance of tactile sensing while Harburg pushes for low cost, soft grippers with no on-board sensors.

In this episode, Ron Vanderkley spoke to Dr Moritz Tenorth, head of software development at Magazino, a Munich-based startup developing mobile pick-and-place robots for item-specific logistics. They discussed his work on the Toru robot and what it means to the warehouse industry today and in the future.

So – you’ve built a robot arm. Now you’ve got to figure out how to control the thing. This was the situation I found myself in a few months ago, during my Masters project, and it’s a problem common to any robotic application: you want to put the end (specifically, the “end effector”) of your robot arm in a certain place, and to do that you have to figure out a valid pose for the arm which achieves that. This problem is called inverse kinematics (IK), and it’s one of the key problems in robotics.