AIRoA MoMa Dataset: A Large-Scale Hierarchical Dataset for Mobile Manipulation
arXiv • 2025
We present the AIRoA MoMa Dataset, a large-scale hierarchical dataset designed to advance research in mobile manipulation within indoor environments.
Publications
You can also find my articles on my Google Scholar profile.
Open-Vocabulary Mobile Manipulation Based on Double Relaxed Contrastive Learning With Dense Labeling
IEEE RA-L • 2025
In this study we propose RelaX-Former, a method that leverages unlabeled positive labels and introduces a double relaxed contrastive learning approach to handle unlabeled positive and negative samples, improving the alignment between images and text.
Mobile Manipulation Instruction Generation from Multiple Images with Automatic Metric Enhancement
IEEE RA-L • 2025
In this study we propose a novel training method that leverages both learning-based and n-gram based automatic evaluation metrics as rewards to generate free-form mobile manipulation instructions.