collaborators

6 papers

cs.CV2026

ECoSim: Data Efficient Fine-Tuning for Controllable Traffic Simulation

Yu-Hsiang Chen, Wei-Jer Chang, Yi-Ting Chen +1

Controllable traffic simulation is critical for testing autonomous driving systems, yet existing approaches often require retraining large generative models with extensive annotate…

cs.RO2026

GRITS: A Spillage-Aware Guided Diffusion Policy for Robot Food Scooping Tasks

Yen-Ling Tai, Yi-Ru Yang, Kuan-Ting Yu +2

Robotic food scooping is a critical manipulation skill for food preparation and service robots. However, existing robot learning algorithms, especially learn-from-demonstration met…

cs.RO2026

HetroD: A High-Fidelity Drone Dataset and Benchmark for Autonomous Driving in Heterogeneous Traffic

Yu-Hsiang Chen, Wei-Jer Chang, Christian Kotulla +7

We present HetroD, a dataset and benchmark for developing autonomous driving systems in heterogeneous environments. HetroD targets the critical challenge of navi- gating real-world…

cs.RO2025

Mitigating Cross-Modal Distraction and Ensuring Geometric Feasibility via Affordance-Guided and Self-Consistent MLLMs for Task Planning in Instruction-Following Manipulation

Yu-Hong Shen, Chuan-Yu Wu, Yi-Ru Yang +2

We investigate the use of Multimodal Large Language Models (MLLMs) with in-context learning for closed-loop task planning in instruction-following manipulation. We identify four es…

cs.CV2025

Task-Oriented Human Grasp Synthesis via Context- and Task-Aware Diffusers

An-Lun Liu, Yu-Wei Chao, Yi-Ting Chen

In this paper, we study task-oriented human grasp synthesis, a new grasp synthesis task that demands both task and context awareness. At the core of our method is the task-aware co…

cs.RO2025

ArticuBot: Learning Universal Articulated Object Manipulation Policy via Large Scale Simulation

Yufei Wang, Ziyu Wang, Mino Nakura +5

This paper presents ArticuBot, in which a single learned policy enables a robotics system to open diverse categories of unseen articulated objects in the real world. This task has…