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cs.RO2025

Improving Robotic Manipulation with Efficient Geometry-Aware Vision Encoder

An Dinh Vuong, Minh Nhat Vu, Ian Reid

Existing RGB-based imitation learning approaches typically employ traditional vision encoders such as ResNet or ViT, which lack explicit 3D reasoning capabilities. Recent geometry-…

cs.RO2025

Lang2Lift: A Language-Guided Autonomous Forklift System for Outdoor Industrial Pallet Handling

Huy Hoang Nguyen, Johannes Huemer, Markus Murschitz +3

Automating pallet handling in outdoor logistics and construction environments remains challenging due to unstructured scenes, variable pallet configurations, and changing environme…

cs.RO2025

Generating Actionable Robot Knowledge Bases by Combining 3D Scene Graphs with Robot Ontologies

Giang Nguyen, Mihai Pomarlan, Sascha Jongebloed +3

In robotics, the effective integration of environmental data into actionable knowledge remains a significant challenge due to the variety and incompatibility of data formats common…

cs.RO2025

Learning Swing-up Maneuvers for a Suspended Aerial Manipulation Platform in a Hierarchical Control Framework

Hemjyoti Das, Minh Nhat Vu, Christian Ott

In this work, we present a novel approach to augment a model-based control method with a reinforcement learning (RL) agent and demonstrate a swing-up maneuver with a suspended aeri…

cs.RO2025

ReFineVLA: Reasoning-Aware Teacher-Guided Transfer Fine-Tuning

Tuan Van Vo, Tan Quang Nguyen, Khang Minh Nguyen +2

Vision-Language-Action (VLA) models have gained much attention from the research community thanks to their strength in translating multimodal observations with linguistic instructi…

cs.RO2025

Action Tokenizer Matters in In-Context Imitation Learning

An Dinh Vuong, Minh Nhat Vu, Dong An +1

In-context imitation learning (ICIL) is a new paradigm that enables robots to generalize from demonstrations to unseen tasks without retraining. A well-structured action representa…