Tag Archives: object
#436426 Video Friday: This Robot Refuses to Fall ...
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
Let us know if you have suggestions for next week, and enjoy today’s videos.
In case you somehow missed the massive Skydio 2 review we posted earlier this week, the first batches of the drone are now shipping. Each drone gets a lot of attention before it goes out the door, and here’s a behind-the-scenes clip of the process.
[ Skydio ]
Sphero RVR is one of the 15 robots on our robot gift guide this year. Here’s a new video Sphero just released showing some of the things you can do with the robot.
[ RVR ]
NimbRo-OP2 has some impressive recovery skills from the obligatory research-motivated robot abuse.
[ NimbRo ]
Teams seeking to qualify for the Virtual Urban Circuit of the Subterranean Challenge can access practice worlds to test their approaches prior to submitting solutions for the competition. This video previews three of the practice environments.
[ DARPA SubT ]
Stretchable skin-like robots that can be rolled up and put in your pocket have been developed by a University of Bristol team using a new way of embedding artificial muscles and electrical adhesion into soft materials.
[ Bristol ]
Happy Holidays from ABB!
Helping New York celebrate the festive season, twelve ABB robots are interacting with visitors to Bloomingdale’s iconic holiday celebration at their 59th Street flagship store. ABB’s robots are the main attraction in three of Bloomingdale’s twelve-holiday window displays at Lexington and Third Avenue, as ABB demonstrates the potential for its robotics and automation technology to revolutionize visual merchandising and make the retail experience more dynamic and whimsical.
[ ABB ]
We introduce pelican eel–inspired dual-morphing architectures that embody quasi-sequential behaviors of origami unfolding and skin stretching in response to fluid pressure. In the proposed system, fluid paths were enclosed and guided by a set of entirely stretchable origami units that imitate the morphing principle of the pelican eel’s stretchable and foldable frames. This geometric and elastomeric design of fluid networks, in which fluid pressure acts in the direction that the whole body deploys first, resulted in a quasi-sequential dual-morphing response. To verify the effectiveness of our design rule, we built an artificial creature mimicking a pelican eel and reproduced biomimetic dual-morphing behavior.
And here’s a real pelican eel:
[ Science Robotics ]
Delft Dynamics’ updated anti-drone system involves a tether, mid-air net gun, and even a parachute.
[ Delft Dynamics ]
Teleoperation is a great way of helping robots with complex tasks, especially if you can do it through motion capture. But what if you’re teleoperating a non-anthropomorphic robot? Columbia’s ROAM Lab is working on it.
[ Paper ] via [ ROAM Lab ]
I don’t know how I missed this video last year because it’s got a steely robot hand squeezing a cute lil’ chick.
[ MotionLib ] via [ RobotStart ]
In this video we present results of a trajectory generation method for autonomous overtaking of unexpected obstacles in a dynamic urban environment. In these settings, blind spots can arise from perception limitations. For example when overtaking unexpected objects on the vehicle’s ego lane on a two-way street. In this case, a human driver would first make sure that the opposite lane is free and that there is enough room to successfully execute the maneuver, and then it would cut into the opposite lane in order to execute the maneuver successfully. We consider the practical problem of autonomous overtaking when the coverage of the perception system is impaired due to occlusion.
[ Paper ]
New weirdness from Toio!
[ Toio ]
Palo Alto City Library won a technology innovation award! Watch to see how Senior Librarian Dan Lou is using Misty to enhance their technology programs to inspire and educate customers.
[ Misty Robotics ]
We consider the problem of reorienting a rigid object with arbitrary known shape on a table using a two-finger pinch gripper. Reorienting problem is challenging because of its non-smoothness and high dimensionality. In this work, we focus on solving reorienting using pivoting, in which we allow the grasped object to rotate between fingers. Pivoting decouples the gripper rotation from the object motion, making it possible to reorient an object under strict robot workspace constraints.
[ CMU ]
How can a mobile robot be a good pedestrian without bumping into you on the sidewalk? It must be hard for a robot to navigate in crowded environments since the flow of traffic follows implied social rules. But researchers from MIT developed an algorithm that teaches mobile robots to maneuver in crowds of people, respecting their natural behaviour.
[ Roboy Research Reviews ]
What happens when humans and robots make art together? In this awe-inspiring talk, artist Sougwen Chung shows how she “taught” her artistic style to a machine — and shares the results of their collaboration after making an unexpected discovery: robots make mistakes, too. “Part of the beauty of human and machine systems is their inherent, shared fallibility,” she says.
[ TED ]
Last month at the Cooper Union in New York City, IEEE TechEthics hosted a public panel session on the facts and misperceptions of autonomous vehicles, part of the IEEE TechEthics Conversations Series. The speakers were: Jason Borenstein from Georgia Tech; Missy Cummings from Duke University; Jack Pokrzywa from SAE; and Heather M. Roff from Johns Hopkins Applied Physics Laboratory. The panel was moderated by Mark A. Vasquez, program manager for IEEE TechEthics.
[ IEEE TechEthics ]
Two videos this week from Lex Fridman’s AI podcast: Noam Chomsky, and Whitney Cummings.
[ AI Podcast ]
This week’s CMU RI Seminar comes from Jeff Clune at the University of Wyoming, on “Improving Robot and Deep Reinforcement Learning via Quality Diversity and Open-Ended Algorithms.”
Quality Diversity (QD) algorithms are those that seek to produce a diverse set of high-performing solutions to problems. I will describe them and a number of their positive attributes. I will then summarize our Nature paper on how they, when combined with Bayesian Optimization, produce a learning algorithm that enables robots, after being damaged, to adapt in 1-2 minutes in order to continue performing their mission, yielding state-of-the-art robot damage recovery. I will next describe our QD-based Go-Explore algorithm, which dramatically improves the ability of deep reinforcement learning algorithms to solve previously unsolvable problems wherein reward signals are sparse, meaning that intelligent exploration is required. Go-Explore solves Montezuma’s Revenge, considered by many to be a major AI research challenge. Finally, I will motivate research into open-ended algorithms, which seek to innovate endlessly, and introduce our POET algorithm, which generates its own training challenges while learning to solve them, automatically creating a curricula for robots to learn an expanding set of diverse skills. POET creates and solves challenges that are unsolvable with traditional deep reinforcement learning techniques.
[ CMU RI ] Continue reading
#436202 Trump CTO Addresses AI, Facial ...
Michael Kratsios, the Chief Technology Officer of the United States, took the stage at Stanford University last week to field questions from Stanford’s Eileen Donahoe and attendees at the 2019 Fall Conference of the Institute for Human-Centered Artificial Intelligence (HAI).
Kratsios, the fourth to hold the U.S. CTO position since its creation by President Barack Obama in 2009, was confirmed in August as President Donald Trump’s first CTO. Before joining the Trump administration, he was chief of staff at investment firm Thiel Capital and chief financial officer of hedge fund Clarium Capital. Donahoe is Executive Director of Stanford’s Global Digital Policy Incubator and served as the first U.S. Ambassador to the United Nations Human Rights Council during the Obama Administration.
The conversation jumped around, hitting on both accomplishments and controversies. Kratsios touted the administration’s success in fixing policy around the use of drones, its memorandum on STEM education, and an increase in funding for basic research in AI—though the magnitude of that increase wasn’t specified. He pointed out that the Trump administration’s AI policy has been a continuation of the policies of the Obama administration, and will continue to build on that foundation. As proof of this, he pointed to Trump’s signing of the American AI Initiative earlier this year. That executive order, Kratsios said, was intended to bring various government agencies together to coordinate their AI efforts and to push the idea that AI is a tool for the American worker. The AI Initiative, he noted, also took into consideration that AI will cause job displacement, and asked private companies to pledge to retrain workers.
The administration, he said, is also looking to remove barriers to AI innovation. In service of that goal, the government will, in the next month or so, release a regulatory guidance memo instructing government agencies about “how they should think about AI technologies,” said Kratsios.
U.S. vs China in AI
A few of the exchanges between Kratsios and Donahoe hit on current hot topics, starting with the tension between the U.S. and China.
Donahoe:
“You talk a lot about unique U.S. ecosystem. In which aspect of AI is the U.S. dominant, and where is China challenging us in dominance?
Kratsios:
“They are challenging us on machine vision. They have more data to work with, given that they have surveillance data.”
Donahoe:
“To what extent would you say the quantity of data collected and available will be a determining factor in AI dominance?”
Kratsios:
“It makes a big difference in the short term. But we do research on how we get over these data humps. There is a future where you don’t need as much data, a lot of federal grants are going to [research in] how you can train models using less data.”
Donahoe turned the conversation to a different tension—that between innovation and values.
Donahoe:
“A lot of conversation yesterday was about the tension between innovation and values, and how do you hold those things together and lead in both realms.”
Kratsios:
“We recognized that the U.S. hadn’t signed on to principles around developing AI. In May, we signed [the Organization for Economic Cooperation and Development Principles on Artificial Intelligence], coming together with other Western democracies to say that these are values that we hold dear.
[Meanwhile,] we have adversaries around the world using AI to surveil people, to suppress human rights. That is why American leadership is so critical: We want to come out with the next great product. And we want our values to underpin the use cases.”
A member of the audience pushed further:
“Maintaining U.S. leadership in AI might have costs in terms of individuals and society. What costs should individuals and society bear to maintain leadership?”
Kratsios:
“I don’t view the world that way. Our companies big and small do not hesitate to talk about the values that underpin their technology. [That is] markedly different from the way our adversaries think. The alternatives are so dire [that we] need to push efforts to bake the values that we hold dear into this technology.”
Facial recognition
And then the conversation turned to the use of AI for facial recognition, an application which (at least for police and other government agencies) was recently banned in San Francisco.
Donahoe:
“Some private sector companies have called for government regulation of facial recognition, and there already are some instances of local governments regulating it. Do you expect federal regulation of facial recognition anytime soon? If not, what ought the parameters be?”
Kratsios:
“A patchwork of regulation of technology is not beneficial for the country. We want to avoid that. Facial recognition has important roles—for example, finding lost or displaced children. There are use cases, but they need to be underpinned by values.”
A member of the audience followed up on that topic, referring to some data presented earlier at the HAI conference on bias in AI:
“Frequently the example of finding missing children is given as the example of why we should not restrict use of facial recognition. But we saw Joy Buolamwini’s presentation on bias in data. I would like to hear your thoughts about how government thinks we should use facial recognition, knowing about this bias.”
Kratsios:
“Fairness, accountability, and robustness are things we want to bake into any technology—not just facial recognition—as we build rules governing use cases.”
Immigration and innovation
A member of the audience brought up the issue of immigration:
“One major pillar of innovation is immigration, does your office advocate for it?”
Kratsios:
“Our office pushes for best and brightest people from around the world to come to work here and study here. There are a few efforts we have made to move towards a more merit-based immigration system, without congressional action. [For example, in] the H1-B visa system, you go through two lotteries. We switched the order of them in order to get more people with advanced degrees through.”
The government’s tech infrastructure
Donahoe brought the conversation around to the tech infrastructure of the government itself:
“We talk about the shiny object, AI, but the 80 percent is the unsexy stuff, at federal and state levels. We don’t have a modern digital infrastructure to enable all the services—like a research cloud. How do we create this digital infrastructure?”
Kratsios:
“I couldn’t agree more; the least partisan issue in Washington is about modernizing IT infrastructure. We spend like $85 billion a year on IT at the federal level, we can certainly do a better job of using those dollars.” Continue reading