Zeya Yin — accepted AI-conference papers

2025

Diverse Motion Planning with Stein Diffusion Trajectory Inference

Zeya Yin, Tin Lai, Lucas Barcelos, Jayadeep Jacob, Yonghui Li, Fabio Ramos

ICRA 2025

Acquiring prior knowledge of trajectory distributions in specific environments can significantly expedite the optimisation process in robot motion planning. Leveraging successful past plans and utilising trajectory generative models as priors offers a clear advantage. Previous studies have proposed

Cited by 6 Source ↗Scholar ↗

2024

Stein Movement Primitives for Adaptive Multi-Modal Trajectory Generation

Zeya Yin, Tin Lai, Subhan Khan, Jayadeep Jacob, Yonghui Li, Fabio Ramos

IROS 2024poster

Probabilistic Movement Primitives (ProMPs) and their variants are powerful methods for enabling robots to learn complex tasks from human demonstrations, where motion trajectories are represented as stochastic processes with Gaussian assumptions. However, despite their computational efficiency, these…

Cited by 0 Source ↗Scholar ↗