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Jaime Fernández Fisac

7 accepted papers

2025

Safety with Agency: Human-Centered Safety Filter with Application to AI-Assisted Motorsports

Donggeon David Oh, Justin Lidard, Haimin Hu, Himani Sinhmar, Elle Lazarski, Deepak Edakkattil Gopinath +5
RSS 2025poster

Recent advances in safe autonomy open new opportunities in assisting humans in safety-critical and time-sensitive tasks such as motorsports. However, existing safe control algorithms predominantly focus on fully automated settings and often undermine key requirements in human–AI shared control domai…

Cited by 0PDF ↗Scholar ↗
2025

Think Deep and Fast: Learning Neural Nonlinear Opinion Dynamics from Inverse Dynamic Games for Split-Second Interactions

Haimin Hu, Jaime Fernández Fisac, Naomi Ehrich Leonard, Deepak E. Gopinath, Jonathan A. DeCastro, Guy Rosman
ICRA 2025

Non-cooperative interactions commonly occur in multi-agent scenarios such as car racing, where an ego vehicle can choose to overtake the rival, or stay behind it until a safe overtaking “corridor” opens. While an expert human can do well at making such time-sensitive decisions, autonomous agents are

Cited by 9Source ↗Scholar ↗
2024

Blending Data-Driven Priors in Dynamic Games

Justin Lidard, Haimin Hu, Asher Hancock, Zixu Zhang, Albert Gimo Contreras, Vikash Modi +6
RSS 2024poster

As intelligent robots like autonomous vehicles become increasingly deployed in the presence of people, the extent to which these systems should leverage model-based game-theoretic planners versus data-driven policies for safe, interaction-aware motion planning remains an open question. Existing dyna…

Cited by 9Source ↗PDF ↗code ↗Scholar ↗
2024

Gameplay Filters: Robust Zero-Shot Safety through Adversarial Imagination

Duy Phuong Nguyen, Kai-Chieh Hsu, Wenhao Yu, Jie Tan, Jaime Fernández Fisac
CoRL 2024poster

Despite the impressive recent advances in learning-based robot control, ensuring robustness to out-of-distribution conditions remains an open challenge. Safety filters can, in principle, keep arbitrary control policies from incurring catastrophic failures by overriding unsafe actions, but existing s…

Cited by 7Source ↗Scholar ↗
2024

Introspective Planning: Aligning Robots' Uncertainty with Inherent Task Ambiguity

Kaiqu Liang, Zixu Zhang, Jaime Fernández Fisac
NeurIPS 2024poster

Large language models (LLMs) exhibit advanced reasoning skills, enabling robots to comprehend natural language instructions and strategically plan high-level actions through proper grounding. However, LLM hallucination may result in robots confidently executing plans that are misaligned with user go…

Cited by 3Source ↗PDF ↗code ↗Scholar ↗
2024

Who Plays First? Optimizing the Order of Play in Stackelberg Games with Many Robots

Haimin Hu, Gabriele Dragotto, Zixu Zhang, Kaiqu Liang, Bartolomeo Stellato, Jaime Fernández Fisac
RSS 2024poster

We consider the multi-agent spatial navigation problem of computing the socially optimal order of play, i.e., the sequence in which the agents commit to their decisions, and its associated equilibrium in an N-player Stackelberg trajectory game. We model this problem as a mixed-integer optimization p…

Cited by 4Source ↗PDF ↗code ↗Scholar ↗
2023

Deception Game: Closing the Safety-Learning Loop in Interactive Robot Autonomy

Haimin Hu, Zixu Zhang, Kensuke Nakamura, Andrea Bajcsy, Jaime Fernández Fisac
CoRL 2023poster

An outstanding challenge for the widespread deployment of robotic systems like autonomous vehicles is ensuring safe interaction with humans without sacrificing performance. Existing safety methods often neglect the robot’s ability to learn and adapt at runtime, leading to overly conservative behavio…

Cited by 16Source ↗Scholar ↗