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Posts published in “Robotics”

Announcing the Embodied AI Workshop #4 at CVPR 2023

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Hey folks, I am proud to announce the 4th annual Embodied AI Workshop, held once again at CVPR 2023! EAI is a multidisciplinary workshop bringing computer vision researchers, machine learning researchers and roboticists to study the problem of creating intelligent systems that interact with their worlds.

For a highlight of previous workshops, see our Retrospectives paper. This year, EAI #4 will feature dozens of researchers, over twenty participating institutions, and ten distinct embodied AI challenges. Our three main themes for this year's workshop are:

  • Foundation Models: large, pretrained models that can solve many tasks few-shot or zero-shot
  • Generalist Agents: agents capable of solving a wide variety of problems
  • Sim to Real Transfer: learning in simulation but deploying in reality.

We will have presentations from all the challenges discussing their tasks, progress in the community, and winning approaches. We will also have six speakers on a variety of topics, and at the end of the workshop I'll be moderating a panel discussion among them.

I hope you can join us, in the real or virtually, at EAI #4 at CVPR 2023 in Vancouver!

-the Centaur

[thirty-nine] minus twenty-one: what a team effort

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Wow. We're done with the paper. And what a team effort! So many people came together on this one - research, infra, operations, human-robot interaction folks, the whole nine yards. It's amazing to me how interdisciplinary robotics is becoming. A few years ago 7 authors on a paper was unusual. But out of the last 5 papers I helped submit, the two shortest papers had 8 authors, and all the others were 15 or more.

And it's not citation inflation. True, this most recent paper had a smaller set of authors actively working on the draft, collating contributions from a larger group running the experiments ... but the previous paper had more than 25 authors, all of whom materially contributed content directly to the draft.

What a wonderful time to be alive.

And to recover from food poisoning.

-the Centaur

Pictured: this afternoon's draft of the paper, just prior to a video conference to hammer out some details.

[twenty-eight] minus twenty: re-ju-ven-ate!

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Oh, look, it's a Dalek acting as a security guard! Nothing can go wrong with this trend. :-/

Though, as a roboticist seeing this gap between terminals, I can't help but wonder whether it just undocked from its charger, whether it is about to dock with its charger, whether it needs help from a human to dock with its charger, or whether it has failed to dock with its charger and is about to run out of power in the dark and the cold where all the wolves are.

-the Centaur

Announcing Logical Robotics

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So, I'm proud to announce my next venture: Logical Robotics, a robot intelligence firm focused on making learning robots work better for people. My research agenda is to combine the latest advances of deep learning with the rich history of classical artificial intelligence, using human-robot interaction research and my years of experience working on products and benchmarking to help robots make a positive impact.

Recent advances in large language model planning, combined with deep learning of robotic skills, have enabled almost magical developments in explainable artificial intelligence, where it is now possible to ask robots to do things in plain language and for the robots to write their own programs to accomplish those goals, building on deep learned skills but reporting results back in plain language. But applying these technologies to real problems will require a deep understanding of both robot performance benchmarks to refine those skills and human psychological studies to evaluate how these systems benefit human users, particularly in the areas of social robotics where robots work in crowds of people.

Logical Robotics will begin accepting new clients in May, after my obligations to my previous employer have come to a close (and I have taken a break after 17 years of work at the Search Engine That Starts With a G). In the meantime, I am available to answer general questions about what we'll be doing; if you're interested, please feel free to drop me a line at via centaur at logicalrobotics.com or take a look at our website.

-the Centaur

do, or do not. there is no blog

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One reason blogging suffers for me is that I always prioritize doing over blogging. That sounds cool and all, but it's actually just another excuse. There's always something more important than doing your laundry ... until you run out of underwear. Blogging has no such hard failure mode, so it's even easier to fall out of the habit. But the reality is, just like laundry, if you set aside a little time for it, you can stay ahead - and you'll feel much healthier and more comfortable if you do.

-the Centaur

Pictured: "Now That's A Steak Burger", a 1-pound monster from Willard Hicks, where I took a break from my million other tasks to catch up on Plans and the Structure of Behavior, the book that introduced idea of the test-operate-test-exit (TOTE) loop as a means for organizing behavior, a device I'm finding useful as I delve into the new field of large language model planning.

Robots in Montreal

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A cool hotel in old Montreal.

"Robots in Montreal," eh? Sounds like the title of a Steven Moffat Doctor Who episode. But it's really ICRA 2019 - the IEEE Conference on Robotics and Automation, and, yes, there are quite a few robots!

Boston Dynamics quadruped robot with arm and another quadruped.

My team presented our work on evolutionary learning of rewards for deep reinforcement learning, AutoRL, on Monday. In an hour or so, I'll be giving a keynote on "Systematizing Robot Navigation with AutoRL":

Keynote: Dr. Anthony Francis
Systematizing Robot Navigation with AutoRL: Evolving Better Policies with Better Evaluation

Abstract: Rigorous scientific evaluation of robot control methods helps the field progress towards better solutions, but deploying methods on robots requires its own kind of rigor. A systematic approach to deployment can do more than just make robots safer, more reliable, and more debuggable; with appropriate machine learning support, it can also improve robot control algorithms themselves. In this talk, we describe our evolutionary reward learning framework AutoRL and our evaluation framework for navigation tasks, and show how improving evaluation of navigation systems can measurably improve the performance of both our evolutionary learner and the navigation policies that it produces. We hope that this starts a conversation about how robotic deployment and scientific advancement can become better mutually reinforcing partners.

Bio: Dr. Anthony G. Francis, Jr. is a Senior Software Engineer at Google Brain Robotics specializing in reinforcement learning for robot navigation. Previously, he worked on emotional long-term memory for robot pets at Georgia Tech's PEPE robot pet project, on models of human memory for information retrieval at Enkia Corporation, and on large-scale metadata search and 3D object visualization at Google. He earned his B.S. (1991), M.S. (1996) and Ph.D. (2000) in Computer Science from Georgia Tech, along with a Certificate in Cognitive Science (1999). He and his colleagues won the ICRA 2018 Best Paper Award for Service Robotics for their paper "PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-based Planning". He's the author of over a dozen peer-reviewed publications and is an inventor on over a half-dozen patents. He's published over a dozen short stories and four novels, including the EPIC eBook Award-winning Frost Moon; his popular writing on robotics includes articles in the books Star Trek Psychology and Westworld Psychology. as well as a Google AI blog article titled Maybe your computer just needs a hug. He lives in San Jose with his wife and cats, but his heart will always belong in Atlanta. You can find out more about his writing at his website.

Looks like I'm on in 15 minutes! Wish me luck.

-the Centaur

 

Viiictory the Fifteenth

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Print

Once again, I’ve completed the challenge of writing 50,000 words in a month as part of the National Novel Writing Month challenges - this time, the July 2016 Camp Nanowrimo, and the next 50,000 words of Dakota Frost #5, PHANTOM SILVER!


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This is the reason that I’ve been so far behind on posting on my blog - I simultaneously was working on four projects: edits on THE CLOCKWORK TIME MACHINE, writing PHANTOM SILVER, doing publishing work for Thinking Ink Press, and doing my part at work-work to help bring about the robot apocalypse (it’s busy work, let me tell you). So busy that I didn’t even blog successfully getting TCTM back to the editor. Add to that a much needed old-friends recharge trip to Tahoe kicking off the month, and I ended up more behind than I’ve ever been … at least, as far as I’ve been behind, and still won:

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What did I learn this time? Well, I can write over 9,000 words a day, though the text often contains more outline than story; I will frequently stop and do GMC (Goal Motivation Conflict) breakdowns of all the characters in the scene and just leave it in the document as paragraphs of italicized notes, because Nano - I can take it out later, its word count now now now! That’s how you get five times a normal word count in a day, or 500+ times the least productive day in which I actually wrote something.

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Also, I get really really really sloppy - normally I wordsmith what I write as I write, even in Nano - but that’s when I have the luxury of writing 1000-2000 words a day. When I have to write 9000, I write things like "I want someoent bo elive this whnen ai Mideone” and just keep going, knowing that I can correct the text later to “I want someone to believe this when I am done,” and, more importantly, can use the idea behind that text to craft a better scene on the next draft (in this case, Dakota’s cameraman Ron is filming a bizarre event in which someone’s life is at stake, and when challenged by a bystander he challenges back, saying that he doesn’t have any useful role to fill, but he can at least document what’s happening so they’ll all be believed later).

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The other thing is, what I am starting to call The Process actually seems to work. I put characters in situations. I think through how they would react, using Goal Motivation Conflict to pull out what they want, why they want it, and why they can’t get it (a method recommended by my editor Debra Dixon in her GMC book). But the critical part of my Process is, when I have to go write something that I don’t know, I look it up - in a lot of detail. Yes, Virginia, even when I was writing 9,000+ words a day, I still went on Wikipedia - and I don’t regret it. Why? Because when I’m spewing around trying to make characters react like they’re in a play, the characters are just emoting, and the beats, no matter how well motivated, could get replaced by something else.

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But when it strikes me that the place my characters area about visit looks like a basilica, I can do more than just write “basilica.” I can ask myself why I chose that word. I can look up the word “basilica” on Apple’s Dictionary app. I can drill through to famous basilicas like the Basilica of Saint Peter. I can think about how this place will be different from that, and start pulling out telling details. I can start to craft a space, to create staging, to create an environment that my characters can react to. Because emotions aren’t just inside us, or between us; they’re for something, for navigating this complex world with other humans at our side. If a group of people argues, no matter how charged, it’s just a soap opera. Put them in their own Germanic/Appalachian heritage family kitchen in the Dark Corner of South Carolina, on on the meditation path near an onsen run continuously by the same family for 42 generations, and the same argument can have a completely different ambiance - and completely different reactions.

The text I wrote using my characters reacting to the past plot, or even with GMC, may likely need a lot of tweaking: the point was to get them to a particular emotional, conceptual or plot space. The text I wrote with the characters reacting to things that were real, even if it needs tweaking, often crackles off the page, even in very rough form. It’s material I won’t want to lose - more importantly, material I wouldn’t have produced, if I hadn’t pushed myself to do National Novel Writing Month.

Up next, finishing a few notes and ideas - the book is very close to done - and then diving into contracts for Thinking Ink Press, and reinforcement learning policy gradients for the robot apocalypse, all while waiting for the shoe to drop on TCTM. Keep your fingers crossed that the book is indeed on its way out!

-the Centaur