iRonCub, the jet-powered flying humanoid robot
iRonCub is ready for takeoff.
Image: IIT

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):

ICRA 2020 – June 1-15, 2020 – [Virtual Conference]
RSS 2020 – July 12-16, 2020 – [Virtual Conference]
CLAWAR 2020 – August 24-26, 2020 – [Virtual Conference]
ICUAS 2020 – September 1-4, 2020 – Athens, Greece
ICRES 2020 – September 28-29, 2020 – Taipei, Taiwan
ICSR 2020 – November 14-16, 2020 – Golden, Colorado

Let us know if you have suggestions for next week, and enjoy today’s videos.

ICRA 2020, the world’s best, biggest, longest virtual robotics conference ever, kicked off last Sunday with an all-star panel on a critical topic: “COVID-19: How Can Roboticists Help?”  

Watch other ICRA keynotes on

We’re getting closer! Well, kinda. iRonCub, the jet-powered flying humanoid, is still a simulation for now, but not only are the simulations getting better—the researchers have begun testing real jet engines!

This video shows the latest results on Aerial Humanoid Robotics obtained by the Dynamic Interaction Control Lab at the Italian Institute of Technology. The video simulates robot and jet dynamics, where the latter uses the results obtained in the paper "Modeling, Identification and Control of Model Jet Engines for Jet Powered Robotics" published in IEEE Robotics and Automation Letters.

This video presents the paper entitled "Modeling, Identification and Control of Model Jet Engines for Jet Powered Robotics" published in IEEE Robotics and Automation Letters (Volume: 5 , Issue: 2 , April 2020 ) Page(s): 2070 - 2077. Preprint at​


In a new pair of papers, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) came up with new tools to let robots better perceive what they’re interacting with: the ability to see and classify items, and a softer, delicate touch.


UBTECH’s anti-epidemic solutions greatly relieve the workload of front-line medical staff and cut the consumption of personal protective equipment (PPE).


We demonstrate a method to assess the concrete deterioration in sewers by performing a tactile inspection motion with a sensorized foot of a legged robot.

[ THING ] via [ ANYmal Research ]

Get a closer look at the Virtual competition of the Urban Circuit and how teams can use the simulated environments to better prepare for the physical courses of the Subterranean Challenge.

[ SubT ]

Roboticists at the University of California San Diego have developed flexible feet that can help robots walk up to 40 percent faster on uneven terrain, such as pebbles and wood chips. The work has applications for search-and-rescue missions as well as space exploration.

[ UCSD ]

Thanks Ioana!

Tsuki is a ROS-enabled, highly dynamic quadruped robot developed by Lingkang Zhang.

And as far as we know, Lingkang is still chasing it.

[ Quadruped Tsuki ]

Thanks Lingkang!

Watch this.

This video shows an impressive demo of how YuMi’s superior precision, using precise servo gripper fingers and vacuum suction tool to pick up extremely small parts inside a mechanical watch. The video is not a final application used in production, it is a demo of how such an application can be implemented.

[ ABB ]

Meet Presso, the “5-minute dry cleaning robot.” Can you really call this a robot? We’re not sure. The company says it uses “soft robotics to hold the garment correctly, then clean, sanitize, press and dry under 5 minutes.” The machine was initially designed for use in the hospitality industry, but after adding a disinfectant function for COVID-19, it is now being used on movie and TV sets.

[ Presso ]

The next Mars rover launches next month (!), and here’s a look at some of the instruments on board.

[ JPL ]

Embodied Lead Engineer, Peter Teel, describes why we chose to build Moxie’s computing system from scratch and what makes it so unique.

[ Embodied ]

I did not know that this is where Pepper’s e-stop is. Nice design!

[ Softbank Robotics ]

State of the art in the field of swarm robotics lacks systems capable of absolute decentralization and is hence unable to mimic complex biological swarm systems consisting of simple units. Our research interconnects fields of swarm robotics and computer vision, and introduces novel use of a vision-based method UVDAR for mutual localization in swarm systems, allowing for absolute decentralization found among biological swarm systems. The developed methodology allows us to deploy real-world aerial swarming systems with robots directly localizing each other instead of communicating their states via a communication network, which is a typical bottleneck of current state of the art systems.

[ CVUT ]

I’m almost positive I could not do this task.

It’s easy to pick up objects using YuMi’s integrated vacuum functionality, it also supports ABB Robot’s Conveyor Tracking and Pickmaster 3 functionality, enabling it to track a moving conveyor and pick up objects using vision. Perfect for consumer products handling applications.

[ ABB ]

Cycling safety gestures, such as hand signals and shoulder checks, are an essential part of safe manoeuvring on the road. Child cyclists, in particular, might have difficulties performing safety gestures on the road or even forget about them, given the lack of cycling experience, road distractions and differences in motor and perceptual-motor abilities compared with adults. To support them, we designed two methods to remind about safety gestures while cycling. The first method employs an icon-based reminder in heads-up display (HUD) glasses and the second combines vibration on the handlebar and ambient light in the helmet. We investigated the performance of both methods in a controlled test-track experiment with 18 children using a mid-size tricycle, augmented with a set of sensors to recognize children’s behavior in real time. We found that both systems are successful in reminding children about safety gestures and have their unique advantages and disadvantages.

[ Paper ]

Nathan Sam and Robert “Red” Jensen fabricate and fly a Prandtl-M aircraft at NASA’s Armstrong Flight Research Center in California. The aircraft is the second of three prototypes of varying sizes to provide scientists with options to fly sensors in the Martian atmosphere to collect weather and landing site information for future human exploration of Mars.

[ NASA ]

This is clever: In order to minimize time spent labeling datasets, you can use radar to identify other vehicles, not because the radar can actually recognize other vehicles, but because the radar can recognize other stuff that’s big and moving, which turns out to be almost as good.

[ ICRA Paper ]

Happy 10th birthday to the Natural Robotics Lab at the University of Sheffield.

[ NRL ]

The Conversation (0)

How the U.S. Army Is Turning Robots Into Team Players

Engineers battle the limits of deep learning for battlefield bots

11 min read
Robot with threads near a fallen branch

RoMan, the Army Research Laboratory's robotic manipulator, considers the best way to grasp and move a tree branch at the Adelphi Laboratory Center, in Maryland.

Evan Ackerman

“I should probably not be standing this close," I think to myself, as the robot slowly approaches a large tree branch on the floor in front of me. It's not the size of the branch that makes me nervous—it's that the robot is operating autonomously, and that while I know what it's supposed to do, I'm not entirely sure what it will do. If everything works the way the roboticists at the U.S. Army Research Laboratory (ARL) in Adelphi, Md., expect, the robot will identify the branch, grasp it, and drag it out of the way. These folks know what they're doing, but I've spent enough time around robots that I take a small step backwards anyway.

This article is part of our special report on AI, “The Great AI Reckoning.”

The robot, named RoMan, for Robotic Manipulator, is about the size of a large lawn mower, with a tracked base that helps it handle most kinds of terrain. At the front, it has a squat torso equipped with cameras and depth sensors, as well as a pair of arms that were harvested from a prototype disaster-response robot originally developed at NASA's Jet Propulsion Laboratory for a DARPA robotics competition. RoMan's job today is roadway clearing, a multistep task that ARL wants the robot to complete as autonomously as possible. Instead of instructing the robot to grasp specific objects in specific ways and move them to specific places, the operators tell RoMan to "go clear a path." It's then up to the robot to make all the decisions necessary to achieve that objective.

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