Dongho Kang

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Dongho Kang

Dongho Kang

@eastskykang

Research scientist at @rai_inst. PhD in computer science from @crl_ethz, @eth_en. Legged robotics, character animation, optimal control and RL.

Zurich, Switzerland Katılım Aralık 2017
318 Takip Edilen684 Takipçiler
Dongho Kang retweetledi
RAI Institute
RAI Institute@rai_inst·
Happy #NationalRoboticsWeek! Last year, we gave you a sneak peek at AthenaZero, our robotic manipulator built to tackle dynamic tasks like a human arm. Learn more about how this fast, precise robot can switch in an instant from a gentle touch to high force depending on what the task requires: rai-inst.com/resources/blog…
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Dongho Kang
Dongho Kang@eastskykang·
Can we teach legged robots to understand natural language and gestures? Check out @TaerimYoon_'s work to see how we are training robots to respond to verbal and physical commands, much like training a real dog. Preprint: arxiv.org/abs/2601.08422 Webpage: taerimyoon.me/Teaching-Robot…
Taerim Yoon@TaerimYoon_

Introducing our recent work: 🐶Teaching Robots Like Dogs: Learning Agile Navigation from Luring, Gesture, and Speech We ask a simple question: Can we teach robots the way we teach dogs? Project page: lnkd.in/eWWSJds2

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Dongho Kang
Dongho Kang@eastskykang·
It is remarkable to witness the strides we are making in humanoid robotics by leveraging human data and reinforcement learning. We are seeing significant breakthroughs in replicating behaviors that are not only natural and athletic but also fully steerable.
RAI Institute@rai_inst

Atlas can perform a backflip combo like a gymnast and also walk naturally across a stage. These very different movements are enabled by the whole-body learning framework developed by the RAI Institute and deployed by @BostonDynamics. We’re getting closer to robust, generalist humanoid behaviors that transfer zero-shot from simulation to physical performance: bit.ly/4rcbMYv

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Dongho Kang retweetledi
Boston Dynamics
Boston Dynamics@BostonDynamics·
We’re excited to announce the product version of our Atlas® robot. This enterprise-grade humanoid robot offers impressive strength and range of motion, precise manipulation, and intelligent adaptability—designed to power the new industrial revolution. youtu.be/sd8ivhpjI6g
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Dongho Kang
Dongho Kang@eastskykang·
Visiting the Computer Science and Engineering department at my home uni, @SeoulNatlUni, for the first time in 10 years. I'll be on campus tomorrow (Tuesday) morning around 10:00 AM, thanks to a kind invitation from Prof. Jungdam Won. If you’re around campus, please ping me!
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Jin Cheng
Jin Cheng@catachiii·
📄 Happy to share our recent RA-L paper "Whole-body Inverse Dynamics MPC for Legged Loco-Manipulation"! We introduces a whole-body MPC framework that unifies motion and force planning within a single control layer, which enables physically consistent, emergent behaviors that allow legged robots to tackle complex manipulation tasks. Congrats on Lukas Molnar on his amazing master thesis! Also thanks to all co-authors Gabriele Fadini, @eastskykang, Fatemeh Zargarbashi, @StelianCoros.
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Dongho Kang retweetledi
RAI Institute
RAI Institute@rai_inst·
See Spot perform dynamic whole-body manipulation. Using a combination of reinforcement learning (RL) and sampling-based control, the robot is able to autonomously drag, roll, and stack tires weighing 15 kg (33 lb), well above its maximum arm lift capacity. Learn more about coordinating locomotion and manipulation processes: rai-inst.com/resources/blog…
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Xie Zhaoming
Xie Zhaoming@zhaomingxie·
Spot is playing Ping Pong! Spin is a crucial part of the game, but few robots can handle it. We show receiving and generating significant spin using MPC. Collaboration with David Nguyen and Zulfiqar Zaidi! Video: youtu.be/3GrnkxOeC14?si…. Paper: arxiv.org/pdf/2510.08754.
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Dongho Kang
Dongho Kang@eastskykang·
Again, a huge congratulations to @yarden_as for his excellent leadership on this project. I'm grateful for the opportunity to have contributed alongside such a brilliant team. Witnessing the impact of theoretical advances on practical robotics was a truly rewarding experience.
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Dongho Kang
Dongho Kang@eastskykang·
"SPiDR" offers an elegant solution for training safe policies for sim-to-real transfer without needing any real-world data, making it versatile and easy to integrate with existing pipelines. You can learn more at the project website: yardenas.github.io/spidr/
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Dongho Kang retweetledi
Ayoung
Ayoung@_ayoungk·
We also release some LaTeX sty and bib files used in the handbook. If you are writing an ICRA paper on SLAM, these should be useful. Visit our GitHub repo for details: github.com/SLAM-Handbook-…
Luca Carlone@lucacarlone1

We have completed the SLAM Handbook "From Localization and Mapping to Spatial Intelligence" and released it online: asrl.utias.utoronto.ca/~tdb/slam/ . The handbook will be published by Cambridge University Press. [1/n]

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Dongho Kang
Dongho Kang@eastskykang·
@IntrovertInDis1 @ChongZitaZhang For those choreographed movements with fine details and smoothness, pure reward shaping is never enough. You need a complete pipeline including motion animation synthesis tool, optimization procedure and motion tracking control.
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Dongho Kang
Dongho Kang@eastskykang·
After an incredible journey completing my PhD, I’m starting my next chapter as a research scientist at @rai_inst. I am excited to join the amazing team and contribute to the mission of creating the next generations of intelligent robots.
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Dongho Kang
Dongho Kang@eastskykang·
@ChongZitaZhang Well, we can make the same argument for humanoids. You could easily say that Boston Dynamics already did most of that stuff years ago. If being the first is the only thing that matters, there's really no point of doing that.
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Dongho Kang
Dongho Kang@eastskykang·
@ChongZitaZhang We're talking about a completely different set of goals and a different focus. Demos from Unitree are primarily about power, maneuverability and robustness. But creating the kind of elegant, symmetric motion you see in this demo... that's a whole different story.
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