arXiv subjects

Sebin Jung

Publications and source records attributed to Sebin Jung.

3 recordsLinked to original sources

arXiv2026

Probing Spin Configurations in Exchange-Coupled Magnetic Bilayers with Orthogonal Anisotropies via Anomalous Hall and Nernst Effects

When two ferromagnetic thin films with different magnetic easy axes are coupled via the exchange interaction, the magnetization process becomes nontrivial. In this paper, we demonstrate that three-dimensional magnetization information in such a bilayer system can be accessed electrically by combining measurements of the anomalous Hall effect (AHE) and anomalous Nernst effect (ANE). Specifically, we investigate a CoFe$_2$O$_4$(001)/Fe bilayer, where the insulating nature of CoFe$_2$O$_4$ ensures that these transport measurements selectively probe only the conductive Fe layer. By combining the AHE and ANE results and comparing them with a simple micromagnetic simulation, we probe the magnetic configuration of antiferromagnetically coupled Fe layer and suggest the emergence of a twisted magnetic structure near the interface.

cond-mat.mtrl-sci↗

arXiv2026

Whole-Body Safe Control of Robotic Systems with Koopman Neural Dynamics

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.

cs.RO↗

arXiv2025

SPARK: Safe Protective and Assistive Robot Kit

This paper introduces the Safe Protective and Assistive Robot Kit (SPARK), a comprehensive benchmark designed to ensure safety in humanoid autonomy and teleoperation. Humanoid robots pose significant safety risks due to their physical capabilities of interacting with complex environments. The physical structures of humanoid robots further add complexity to the design of general safety solutions. To facilitate safe deployment of complex robot systems, SPARK can be used as a toolbox that comes with state-of-the-art safe control algorithms in a modular and composable robot control framework. Users can easily configure safety criteria and sensitivity levels to optimize the balance between safety and performance. To accelerate humanoid safety research and development, SPARK provides simulation benchmarks that compare safety approaches in a variety of environments, tasks, and robot models. Furthermore, SPARK allows quick deployment of synthesized safe controllers on real robots. For hardware deployment, SPARK supports Apple Vision Pro (AVP) or a Motion Capture System as external sensors, while offering interfaces for seamless integration with alternative hardware setups at the same time. This paper demonstrates SPARK's capability with both simulation experiments and case studies with a Unitree G1 humanoid robot. Leveraging these advantages of SPARK, users and researchers can significantly improve the safety of their humanoid systems as well as accelerate relevant research. The open source code is available at: https://github.com/intelligent-control-lab/spark.

cs.RO↗