Roberto

Assistant CS Professor at UT Austin. Former Stanford and TUBerlin. Researching at the intersection of vision, learning and robotics 🏳️‍🌈

[Roberto @RobobertoMM]

I'll be giving two talks at ICRA today: 2:30pm on "Frugal Imitation Learning" (beyond telop workshop) and on 5:30pm on "Closing the Understanding Gap Between Humans and Robots" (robot learning + HRI). Come visit!

[Rutav @rutavms]

Can we build generalist robots with zero teleoperation? Come participate in the discussion and weigh in at our ICRA'26 workshop, BeyondTeleop, starting at 8.45 am CEST today (June 5th)!

📍 Strauss 3

[Priyanka Mandikal @PrnkMandikal]

🤖 How can robots learn long-horizon object state change tasks like mashing a banana 🥣🍌, spreading ketchup on bread 🍅🍞, or slicing a cucumber 🔪🥒?

Introducing SPARTA: object state-change manipulation via visual spatial progress 👇

🌐 https://t.co/pzRiSYqHjc

[Luca Macesanu @LucaMacesanu]

Don’t miss our poster at #ICRA!
June 3rd 3-4:30 WeI2I.312 and June 5th 10:45-11:45 in the Uncertainty in Open-World Robotics Workshop!

[Albert Yu @albertyu101]

Robots can’t do everything.

How can they effectively work with us?

We present MiCoBot, a flexible human-robot collaborative framework where both🧑‍🦱+🤖can initiate 💬verbal and🦾physical actions.

To be presented at ICRA tomorrow 6/3!
Poster 9-10:30am @ I.126

(1/8)

[Roberto @RobobertoMM]

How to learn how things sound? Interacting with them! We are presenting CAVER at ICRA, a really fun work

[Luca Macesanu @LucaMacesanu]

Can you guess the object by its sound? 🔊

Humans learn to correlate sight and sound through exploration from infancy. We want robots to learn the same way.

Meet CAVER: the first Curious Audio-Visual Exploring Robot, learning about the world through interactive exploration. 🤖✨

[Arpit Bahety @ArpitBahety]

Excited to announce our #RSS2026 workshop: "Rethinking What It Means to be 'Safe' for Generalist Robots"! 🛡️🤖

Have new work or videos of robot safety failures? Submit by June 12! 👇

[Roberto @RobobertoMM]

How do we turn a decent generalist VLA into a great multitask specialist? RL can turn experience into one fine-tuned policy. The challenge is doing it continuously as new tasks arrive: without forgetting old ones or limiting future learning.
Surprisingly simple. Check this out.

[Jiaheng Hu @JiahengHu1]

VLA models are capable generalists. But can they continually self-improve?

Such Continual Reinforcement Learning (CRL) problems are traditionally considered very challenging.

Surprisingly, we found that with the right setup, the simplest CRL recipe can work really well!

https://t.co/7DmlhAqX9L

[Shivin Dass @ShivinDass]

Excited to share that DataMIL is accepted at ICLR. To celebrate we are also releasing the codebase: https://t.co/Rdh8kitlGq

You can now curate data for your robot within a couple of hours!

[Chengshu Li @ChengshuEricLi]

We are excited to release MoMaGen, a data generation method for multi-step bimanual mobile manipulation.
MoMaGen turns 1 human-teleoped robot trajectory into 1000s of generated trajectories automatically.🚀

Website: https://t.co/DYKvqY4bII
arXiv: https://t.co/lDffi0FXHl

[Shivin Dass @ShivinDass]

A little late to this but excited to share that DataMIL won the best paper at the Data workshop at #CoRL!

If you haven't already, check it out! 👇

[naveen manwani @NaveenManwani17]

🚨CoRL 2025 Best Poster Award 🏆 Paper Alert 🚨

➡️Paper Title: Mash, Spread, Slice! Learning to Manipulate Object States via Visual Spatial Progress

🌟Few pointers from the paper

🎯Most robot manipulation focuses on changing the kinematic state of objects: picking, placing, opening, or rotating them.

🎯However, a wide range of real-world manipulation tasks involve a different class of object state change—such as mashing, spreading, or slicing—where the object’s physical and visual state evolve progressively without necessarily changing its position.

🎯Authors of this paper presented “SPARTA”, the first unified framework for the family of object state change manipulation tasks.

🎯Their key insight is that these tasks share a common structural pattern:they involve spatially-progressing, object-centric changes that can be represented as regions transitioning from an actionable to a transformed state.

🎯Building on this insight, SPARTA integrates spatially progressing object change segmentation maps, a visual skill to perceive actionable vs. transformed regions for specific object state change tasks, to generate

a) structured policy observations that strip away appearance variability,
and
b) dense rewards that capture incremental progress over time.

🎯These are leveraged in two SPARTA policy variants:reinforcement learning for fine-grained control without demonstrations or simulation; and greedy control for fast, lightweight deployment.

🎯They validated “SPARTA” on a real robot for three challenging tasks across 10 diverse real-world objects, achieving significant improvements in training time and accuracy over sparse rewards and visual goal-conditioned baselines.

🎯Their results highlight progress-aware visual representations as a versatile foundation for the broader family of object state manipulation tasks.

🏢Organization: @UTAustin

🧙Paper Authors: Priyanka Mandikal, @JiahengHu1 , @ShivinDass , @sagnikmjr , @RobobertoMM , Kristen Grauman

📝 Read the Full Paper here: https://t.co/JpM2DelaLP

🗂️ Project Page: https://t.co/Od0hWUDVBl

🎥 Be sure to watch the attached Technical Summary Video - Sound on 🔊🔊

Find this Valuable 💎 ?

♻️QT and teach your network something new

Follow me 👣, @NaveenManwani17 , for the latest updates on Tech and AI-related news, insightful research papers, and exciting announcements.

#CoRL2025

[Jiaheng Hu @JiahengHu1]

Excited that SPARTA (https://t.co/AVZTpsbfSw) won the best poster award at the CoRL RINO workshop!

Big congrats to the project lead Priyanka, who worked so hard on this project, as well as to the rest of the co-authors @ShivinDass @sagnikmjr @RobobertoMM and Kristen!

[Gautam Kamath @thegautamkamath]

📢 Call for Community Activities #AAAI2026

We invite submissions of proposals for including and open activities that help broaden community participation in the AI field.

October 4: Submission Deadline
October 18: Acceptance Notifications
@RobobertoMM @marucabrera27 @RealAAAI

[Roberto @RobobertoMM]

Simple but *so effective idea*! And it can be used with any feature data selector. Great work led by @sateeshk21 . Do not miss it at #CoRL2025 (Spotlight 4 & Poster 2 on Sept 29)!

[Sateesh Kumar @sateeshk21]

Which data is best for training few-shot imitation policies for robot manipulation?

Some think it’s the data that looks similar, or has similar motion, or comes with related language labels. They are all right AND wrong: depending on the task, sometimes this similarity helps but sometimes it is detrimental.

Presenting Our #CoRL2025 work, COLLAGE 🎨, that adaptively combine data subsets efficiently for learning effective policies on target tasks.  🧵

[Rutav @rutavms]

Intelligent humanoids should have the ability to quickly adapt to new tasks by observing humans

Why is such adaptability important?
🌍 Real-world diversity is hard to fully capture in advance
🧠 Adaptability is central to natural intelligence

We present MimicDroid 👇

🌐 https://t.co/J8XpND9j1j

[Roberto @RobobertoMM]

Honored to give an Early Career Invited Talk at #IJCAI today. See you at 11:30am in room 520C!

[Roberto @RobobertoMM]

It was time to improve our evaluations in robot learning! We introduce a methodology based on anonymous A/B testing: fairer, stronger, community-driven.
Awesome work by @KarlPertsch @pranav_atreya @tonyh_lee and an incredible crowdsourcing team.
Upload and test your model! 🚀

[Karl Pertsch @KarlPertsch]

We’re releasing the RoboArena today!🤖🦾

Fair & scalable evaluation is a major bottleneck for research on generalist policies. We’re hoping that RoboArena can help!

We provide data, model code & sim evals for debugging! Submit your policies today and join the leaderboard! :)
🧵

[Arpit Bahety @ArpitBahety]

Imagine a future where robots are part of our daily lives — How can end users teach robots new tasks by directly showing them, just like teaching another person?

🧵👇

[Huihan Liu @huihan_liu]

Meet Casper👻, a friendly robot sidekick who shadows your day, decodes your intents on the fly, and lends a hand while you stay in control!

Instead of passively receiving commands, what if a robot actively sense what you need in the background, and step in when confident? (1/n)