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Industrial Automation

interview by   -   April 14, 2018
Toyota HSR Trained with DART to Make a Bed.

In this episode, Audrow Nash speaks with Michael Laskey, PhD student at UC Berkeley, about a method for robust imitation learning, called DART. Laskey discusses how DART relates to previous imitation learning methods, how this approach has been used for folding bed sheets, and on the importance of robotics leveraging theory in other disciplines.

interview by   -   March 31, 2018



In this interview, Audrow speaks with Andrea Bajcsy and Dylan P. Losey about a method that allows robots to infer a human’s objective through physical interaction. They discuss their approach, the challenges of learning complex tasks, and their experience collaborating between different universities.

interview by   -   January 20, 2018



In this episode Abate talks with Zhe Zhang from Perceptin where they are building embedded platforms for robots to do Simultaneous Localization and Mapping (SLAM) algorithms in real time. Zhe explains the methods they incorporate such as sensor fusion and hardware synchronization to make a highly accurate SLAM platform for IOT, consumer, and automotive grade robots.

interview by   -   November 11, 2017



In this interview, Audrow Nash interviews Marco Hutter, Assistant Professor for Robotic Systems at ETH Zürich, about a quadrupedal robot designed for autonomous operation in challenging environments, called ANYmal. Hutter discusses ANYmal’s design, the ARGOS oil and gas rig inspection challenge, and the advantages and complexities of quadrupedal locomotion. 

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Future robots will work side by side with humans, just as they do today.
Credit: AP Photo/John Minchillo

by Thomas Kochan, MIT Sloan School of Management and Lee Dyer, Cornell University

The technologies driving artificial intelligence are expanding exponentially, leading many technology experts and futurists to predict machines will soon be doing many of the jobs that humans do today. Some even predict humans could lose control over their future.

Last week I was talking to one lead engineer of a Singapore company which is building a benchmarking system for robot solutions. Having seen my presentation at ROSCON2016 about robot benchmarking, he asked me how I would benchmark solutions that are non-ROS compatible. I said that I wouldn’t dedicate time to benchmark solutions that are not ROS-based. Instead, I suggested I would use the time to polish the ROS-based benchmarking and suggest that vendors adopt that middleware in their products.

Robot butchers, cake decorator and pizza-baking manipulators. Here are our six favorite robot applications which are changing the food industry.


Sixteen teams from across the globe came to Nagoya, Japan to participate in the third annual Amazon Robotics Challenge. Amazon sponsors the event to strengthen ties between the industrial and academic robotics communities and to promote shared and open solutions to some of the big puzzles in the field. The teams took home $270,000 in prizes.

by   -   July 27, 2017


The Cocktail Bot 4.0 consists of five robots with one high-level goal: Mix one more than 20 possible drink combination for you! But it isn’t as easy as it sounds. After the customer composed his drink by combining liquor, soft drink and ice in a web interface. The robots start to mix the drink on their own. Five robot stations are preparing the order to deliver it to the guests.

By Jeff Morgan, Trinity College Dublin

Robots have been taking our jobs since the 1960s. So why are politicians and business leaders only now becoming so worried about robots causing mass unemployment?

This week features HEPHAESTUS: Highly automatEd PHysical Achievements and performancES using cable roboTs Unique SysHighly automatEd PHysical Achievements and performancES using cable roboTs Unique Systemstems.

The Association for Advancing Automation (A3) cites that between 2010 and 2016, 136,748 robots were shipped to the US —the most in any seven-year period in the US robotics industry. At the same time, US manufacturing employment increased by 894,000 and the unemployment rate fell from 9.8% to 4.7%.

interview by   -   June 24, 2017

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.

Advances in robotics and AI have led to modern commercial drone technology, which is changing the fundamental way enterprises interact with the world. Drones bridge the physical and digital worlds. They enable companies to combine the power of scalable computing resources with pervasive, affordable sensors that can go anywhere. This creates an environment in which businesses can make quick, accurate decisions based on enormous datasets derived from the physical world.

interview by and   -   June 9, 2017
Credit: sk.ru


In this episode, Audrow Nash and Christina Brester conduct interviews at the 2016 International Association of Science Parks and Areas of Innovation conference in Moscow, Russia. They speak with Vadim Kotenev of Rehabot and Motorica about prosthetic hands and rehabilatative devices; and Vagan Martirosyan, CEO of TryFit, a company that uses robotic sensors to help people find shoes that fit them well.



Hyundai’s Exoskeletons
May 14, 2018


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