Juan Alvarez-Padilla — accepted AI-conference papers

2025

ROADWork: A Dataset and Benchmark for Learning to Recognize, Observe, Analyze and Drive Through Work Zones

Anurag Ghosh, Shen Zheng, Robert Tamburo, Khiem Vuong, Juan Alvarez-Padilla, Hailiang Zhu +4

ICCV 2025poster

Perceiving and autonomously navigating through work zones is a challenging and under-explored problem. Open datasets for this long-tailed scenario are scarce. We propose the ROADWork dataset to learn to recognize, observe, analyze, and drive through work zones. State-of-the-art foundation models fai…

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2025

Real-Time Whole-Body Control of Legged Robots with Model-Predictive Path Integral Control

Juan Alvarez-Padilla, John Z. Zhang, Sofia Kwok, John M. Dolan, Zachary Manchester

ICRA 2025

This paper presents a system for enabling real-time synthesis of whole-body locomotion and manipulation policies for real-world legged robots. Motivated by recent advancements in robot simulation, we leverage the efficient parallelization capabilities of the MuJoCo simulator on a multi-core CPU to a

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