Projects

Publications

[C109] Whole-Body Safe Control of Robotic Systems with Koopman Neural Dynamics
Sebin Jung, Abulikemu Abuduweili, Jiaxing Li and Changliu Liu
IEEE International Conference on Robotics and Automation, 2026
Citation Formats:
```
    
```
Abstract:

Controlling robots with strongly nonlinear, high-dimensional dynamics remains challenging, as direct nonlinear optimization with safety constraints is often intractable in real time. The Koopman operator offers a way to represent nonlinear systems linearly in a lifted space, enabling the use of efficient linear control. We propose a data-driven framework that learns a Koopman embedding and operator from data, and integrates the resulting linear model with the Safe Set Algorithm (SSA). This allows the tracking and safety constraints to be solved in a single quadratic program (QP), ensuring feasibility and optimality without a separate safety filter. We validate the method on a Kinova Gen3 manipulator and a Go2 quadruped, showing accurate tracking and obstacle avoidance.

[J37] Verifiable Safety Q-Filters via Hamilton-Jacobi Reachability and Multiplicative Q-Networks
Jiaxing Li, Hanjiang Hu, Yujie Yang and Changliu Liu
IEEE Control Systems Letters, 2025
Citation Formats:
```
    
```
Abstract:

Recent learning-based safety filters have outperformed conventional methods, such as hand-crafted Control Barrier Functions (CBFs), by effectively adapting to complex constraints. However, these learning-based approaches lack formal safety guarantees. In this work, we introduce a verifiable model-free safety filter based on Hamilton-Jacobi reachability analysis. Our primary contributions include: 1) extending verifiable self-consistency properties for Q value functions, 2) proposing a multiplicative Q-network structure to mitigate zero-sublevel-set shrinkage issues, and 3) developing a verification pipeline capable of soundly verifying these self-consistency properties. Our proposed approach successfully synthesizes formally verified, model-free safety certificates across four standard safe-control benchmarks.