🎓 Two more doctors in our lab! We congratulate Bhavya Sukhija @sukhijabhavy and Núria Armengol Urpí @NriaArmengol2 on their successful doctoral defense!
We’re heading to Vienna! 🇦🇹🤖
The Computational Robotics Lab (CRL) @ETH_en is thrilled to present 5 papers at #ICRA2026 next week! We're bringing our latest work on legged loco-manipulation, deformable objects, MPC, and RL.
Drop by our interactive sessions! 👇 Thread 🧵
📄 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.
🖥️ I will present three papers on today's workshop sessions at #CoRL2025. I'm so excited to share these new works to new friends!
RAMBO: RL-augmented Model-based Whole-body Control for Loco-manipulation
at
- 2nd Workshop on Safe and Robust Robot Learning for Operation in the Real World (RAMBO) (Room E1, 🌟best paper)
- Workshop on Resource-Rational Robot Learning (Room E6)
CAIMAN: Causal Action Influence Detection for Sample-efficient Loco-manipulation
at
- Workshop on Resource-Rational Robot Learning (Room E6, ⭐️best paper runner up)
- Robotics World Modeling (Room E4)
Learning More With Less: Sample-Efficient Model-Based RL for Loco-Manipulation
at
- Workshop on Resource-Rational Robot Learning (Room E6)
- Robotics World Modeling (Room E4)
I have successfully defended my dissertation "Animal Motion Imitation For Adaptive and Lifelike Control of Legged Robots" at ETH Zurich. A huge thanks to my supervisors, committee members, amazing collaborators, and peers at CRL @crl_ethz who made this possible!
Last week I presented our last work: 🐝“Epistemically-guided forward backward exploration (FBEE)”🐝 at the @RL_Conference
TLDR: Active learning for unsupervised RL
Happy to share our recent RA-L paper on loco-manipulation. The combination of RL and model-based whole-body controller really pushes the capabilities of legged robots on robustness and precise manipulation.
#AI#robot#unitree#rl#reinforcementlearning#ETH#CMU
🐕 I'm happy to share my paper: RAMBO: RL-augmented Model-based Whole-body Control for Loco-manipulation has been accepted by IEEE Robotics and Automation Letters (RA-L) 🧶
Project website: https://t.co/SV901snEF2
Paper: https://t.co/BWsb8fIiYa
Last Friday, we participated in the annual ETH RobotX Innovation Day. The event began with an inspiring opening by Prof. Stelian Coros. We were proud to share our latest research with the broader ETH robotics community and industry partners.
🎓 Another doctor!
Flavio De Vincenti has successfully defended his doctoral thesis on Optimal and Learning-Based Control for Collaborative Loco-Manipulation! Congratulations!
📈 Historic Finish!
Our lab placed 299th out of 1,106 in SOLA-Stafette 2025!
Congratulations to all participants and a big thank you to our wonderful organizer, @NriaArmengol2!