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Video Friday: India Sending Humanoid Robot Into Space
Image: Times of India via YouTube

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!):

Robotic Arena – January 25, 2020 – Wrocław, Poland
DARPA SubT Urban Circuit – February 18-27, 2020 – Olympia, Wash., USA
HRI 2020 – March 23-26, 2020 – Cambridge, U.K.
ICARSC 2020 – April 15-17, 2020 – Ponta Delgada, Azores
ICRA 2020 – May 31-4, 2020 – Paris, France

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

I’ve got to hand it to Boston Dynamics—letting Adam Savage borrow a Spot for a year is a pretty savvy marketing move.

[ Tested ]

The Indian Space Research Organization (ISRO) plans to send a humanoid robot into space later this year. According to a Times of India story, the humanoid is called Vyommitra and will help ISRO prepare for its Gaganyaan manned space flight mission, expected for 2022. Before sending human astronauts, ISRO will send Vyommitra, which can speak but doesn’t move much (it currently has no legs). According to the Times of IndiaISRO chief Kailasavadivoo Sivan said the “Gaganyaan mission is not just about sending a human to space, this mission provides us an opportunities to build a framework for long term national and international collaborations and cooperation. We all know that scientific discoveries, economic development, education, tech development and inspiring youth are coming goals for all nations. Human space flight provides perfect platform to meet all these objectives.”

[ Times of India ]

Soft robots have applications in safe human-robot interactions, manipulation of fragile objects, and locomotion in challenging and unstructured environments. In this paper, we present a computational method for augmenting soft robots with proprioceptive sensing capabilities. Our method automatically computes a minimal stretch-receptive sensor network to user-provided soft robotic designs, which is optimized to perform well under a set of user-specified deformation-force pairs. The sensorized robots are able to reconstruct their full deformation state, under interaction forces. We cast our sensor design as a sub-selection problem, selecting a minimal set of sensors from a large set of fabricable ones which minimizes the error when sensing specified deformation-force pairs. Unique to our approach is the use of an analytical gradient of our reconstruction performance measure with respect to selection variables. We demonstrate our technique on a bending bar and gripper example, illustrating more complex designs with a simulated tentacle.

Disney Research ]

Dragonfly is a rotorcraft lander that will explore Saturn’s large moon Titan. The sampling system called DrACO (Drill for Acquisition of Complex Organics) will extract material from Titan’s surface and deliver it to DraMS (Dragonfly Mass Spectrometer, provided by NASA Goddard Space Flight Center). Honeybee Robotics will build the end-to-end DrACO system (including hardware, avionics, and flight software) and will command its operation once Dragonfly lands on Titan in 2034.

Honeybee Robotics ]

DARPA’s Gremlins program has completed the first flight test of its X-61A vehicle. The test in late November at the U.S. Army’s Dugway Proving Ground in Utah included one captive-carry mission aboard a C-130A and an airborne launch and free flight lasting just over an hour-and-a-half.

The goal for this third phase of the Gremlins program is completion of a full-scale technology demonstration series featuring the air recovery of multiple, low-cost, reusable unmanned aerial systems (UASs), or “Gremlins.” Safety, reliability, and affordability are the key objectives for the system, which would launch groups of UASs from multiple types of military aircraft while out of range from adversary defenses. Once Gremlins complete their mission, the transport aircraft would retrieve them in the air and carry them home, where ground crews would prepare them for their next use within 24 hours.


Thi is only sort of a robot, more of an automated system, but I like the idea: dog training!

[ CompanionPro ]

Free-falling paper shapes exhibit rich, complex and varied behaviours that are extremely challenging to model analytically. Physical experimentation aids in system understanding, but is time-consuming, sensitive to initial conditions and reliant on subjective visual behavioural classification. In this study, robotics, computer vision and machine learning are used to autonomously fabricate, drop, analyse and classify the behaviours of hundreds of shapes.

[ Nature ]

This paper introduces LiftTiles, modular inflatable actuators for prototyping room-scale shape-changing interfaces. Each inflatable actuator has a large footprint (e.g., 30 cm x 30 cm) and enables large-scale shape transformation. The ac- tuator is fabricated from a flexible plastic tube and constant force springs. It extends when inflated and retracts by the force of its spring when deflated. By controlling the internal air volume, the actuator can change its height from 15 cm to 150 cm.

We designed each module as low cost (e.g., 8 USD), lightweight (e.g., 1.8kg), and robust (e.g., with- stand more than 10 kg weight), so that it is suitable for rapid prototyping of room-sized interfaces. Our design utilizes constant force springs to provide greater scalability, simplified fabrication, and stronger retraction force, all essential for large-scale shape-change.

[ LiftTiles ]

Aibo may not be the most fearsome security pupper, but it does have what other dogs don’t: Wireless connectivity, remote control, and a camera.

[ Aibo ]

I missed this Toyota HSR demo at CES, which is really too bad because I really could have used a snack.

[ NEU ]

The HKUST Aerial Robotics Group has some impressive real-time drone planning that’ll be presented at ICRA 2020:

[ Paper ]

Gripping something tricky? When in doubt, just add more fingers.

[ Soft Robotics ]

Demo of the project of Nino Di Pasquale, Matthieu Le Cauchois, Alejandra Plaice and Joël Zbinden. The goal was to program in Python and combine in a project, elements of global path planning, local path planning, baysian filtering for pose estimation and computer vision. The video presents the visualisation interface in real time, assoicated with the real video of the setting with the Thymio robot controlled by wireless connection by the computer running the program.

[ EPFL ]

From public funding opportunities to the latest technologies in software and system integration, the combination of robotics and IT to hardware and application highlights plus updates on new platforms and open-source communities: ROS-Industrial Conference 2019 offered on 3 days in December a varied and top-class programme to more than 150 attendees.

[ ROS-I Consortium ]

Aaron Johnson and his students have been exploring whether hoof-inspired feet can help robots adapt to rough terrain without needing to exhaustively plan out every step.

There’s no paper or anything yet, but Aaron did give a talk at Dynamic Walking 2018.

[ Robomechanics Lab ]

YouTube has put some money into an original eight-episode series on robots and AI, featuring some well-known roboticists. Here are a couple of the more robot-y episodes:

You can watch the whole series at the link below.

[ Age of AI ]

On the AI Podcast, Lex Fridman speaks with Ayanna Howard from Georgia Tech.

[ Lex Fridman ]

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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