Antonio Loquercio

@antoniloq

Assistant Professor at #UPenn. Mainly interested in #PhysicalAI

Philadelphia antonilo.github.io Joined December 2017

730 Following 2.3K Followers 436 Posts

Latest posts 5

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Antonio Loquercio @antoniloq Dec 12, 2025

We found that training (multi-agent) policies to win a race with sparse competitive rewards leads to agile policies with strategic behaviors. These policies outperform the ones trained with behavioral-prescribing dense rewards and transfer better to the real world.

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Antonio Loquercio @antoniloq Nov 3

It is really impressive what this model can do (in real time!). Maye the time has arrived for a solid real-time MPC with a video model?

Yiming Dou Verified account @_YimingDou Oct 29

Introducing DreamFAR, a world model trained from scratch using only robot data, without internet pretraining. It supports:
🎮 Real-time teleoperation
⏱️ Minutes of long-horizon rollout
🧩 Generalization across 1,000+ tasks

yimingdou.com/DreamFAR

🧵 (1/8)

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Antonio Loquercio @antoniloq Oct 15

Can GPT-6 Astra control an FPV drone, predicting control commands directly from images?
YES! It was very effective at whatever tasks we threw at it, both in single agent and multi-agent settings. Read more in our blog post: jirl-upenn.github.io/blog/astra-as-…

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Antonio Loquercio @antoniloq Dec 4, 2025

Last day of class of my brand-new course Physical Intelligence (lnkd.in/d9BMFG5d) at #UPenn. We concluded with a drone racing competition in the real world!

I am really proud of all the students; I have no doubt that they will do great in the future!

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Antonio Loquercio @antoniloq Nov 13, 2025

🤖🇮🇹🥳

Penn Engineering Verified account @PennEngineers Nov 13, 2025

Congratulations to Antonio Loquercio (@antoniloq) on receiving the 2025 Mario Gerla Young Investigator Award from @issnaf.

Recognized for his research on the pivotal role of perception in building effective world models for decision-making, Loquercio enhances the performance of complex robotic systems. He explores how robots can utilize their own sensor data to refine their world models.

Congratulations, Antonio!

bit.ly/4pbaUSE

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