4 citations · 13 across the 24 of their papers we have counts for
18 papers · 1 filter
Gripper-aware Vision Language Action Models
Hanyi Zhang, Zihong Luo, Tianyu Li +16
Vision language action models (VLAs) have advanced general purpose robotic grasping and manipulation by enabling robots to interpret visual observations and natural language instru…
Beyond Visual Grasping: Benchmarking Complex Grasping from Detection to Execution
Hanyi Zhang, Khang Nguyen, Charith Munasinghe +10
Robust robotic grasping remains a fundamental challenge for complex real-world applications. Recent advances in large-scale models demonstrate promising capabilities for reasoning…
MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction
Zhihao Cao, Qi Shao, Shuhao Zhai +4
Collaborative photorealistic 3D reconstruction from multiple agents enables rapid large-scale scene capture for virtual production and cooperative multi-robot exploration. While re…
AeroScene: Progressive Scene Synthesis for Aerial Robotics
Nghia Vu, Tuong Do, Dzung Tran +6
Generative models have shown substantial impact across multiple domains, their potential for scene synthesis remains underexplored in robotics. This gap is more evident in drone si…
GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System
Quang Nguyen, Tri Le, Huy Nguyen +5
Language-driven grasp detection has the potential to revolutionize human-robot interaction by allowing robots to understand and execute grasping tasks based on natural language com…
Humanoid Agent via Embodied Chain-of-Action Reasoning with Multimodal Foundation Models for Zero-Shot Loco-Manipulation
Congcong Wen, Geeta Chandra Raju Bethala, Yu Hao +8
Humanoid loco-manipulation, which integrates whole-body locomotion with dexterous manipulation, remains a fundamental challenge in robotics. Beyond whole-body coordination and bala…
RoboDesign1M: A Large-scale Dataset for Robot Design Understanding
Tri Le, Toan Nguyen, Quang Tran +6
Robot design is a complex and time-consuming process that requires specialized expertise. Gaining a deeper understanding of robot design data can enable various applications, inclu…
Robotic-CLIP: Fine-tuning CLIP on Action Data for Robotic Applications
Nghia Nguyen, Minh Nhat Vu, Tung D. Ta +4
Vision language models have played a key role in extracting meaningful features for various robotic applications. Among these, Contrastive Language-Image Pretraining (CLIP) is wide…
GraspMamba: A Mamba-based Language-driven Grasp Detection Framework with Hierarchical Feature Learning
Huy Hoang Nguyen, An Vuong, Anh Nguyen +2
Grasp detection is a fundamental robotic task critical to the success of many industrial applications. However, current language-driven models for this task often struggle with clu…
Language-driven Grasp Detection with Mask-guided Attention
Tuan Van Vo, Minh Nhat Vu, Baoru Huang +4
Grasp detection is an essential task in robotics with various industrial applications. However, traditional methods often struggle with occlusions and do not utilize language for g…
Lightweight Language-driven Grasp Detection using Conditional Consistency Model
Nghia Nguyen, Minh Nhat Vu, Baoru Huang +4
Language-driven grasp detection is a fundamental yet challenging task in robotics with various industrial applications. In this work, we present a new approach for language-driven…
Language-Driven 6-DoF Grasp Detection Using Negative Prompt Guidance
Toan Nguyen, Minh Nhat Vu, Baoru Huang +5
6-DoF grasp detection has been a fundamental and challenging problem in robotic vision. While previous works have focused on ensuring grasp stability, they often do not consider hu…
Language-Driven Closed-Loop Grasping with Model-Predictive Trajectory Replanning
Huy Hoang Nguyen, Minh Nhat Vu, Florian Beck +3
Combining a vision module inside a closed-loop control system for a \emph{seamless movement} of a robot in a manipulation task is challenging due to the inconsistent update rates b…
Autonomous Catheterization with Open-source Simulator and Expert Trajectory
Tudor Jianu, Baoru Huang, Tuan Vo +7
Endovascular robots have been actively developed in both academia and industry. However, progress toward autonomous catheterization is often hampered by the widespread use of close…
Open-Vocabulary Affordance Detection using Knowledge Distillation and Text-Point Correlation
Tuan Van Vo, Minh Nhat Vu, Baoru Huang +4
Affordance detection presents intricate challenges and has a wide range of robotic applications. Previous works have faced limitations such as the complexities of 3D object shapes,…
Language-Conditioned Affordance-Pose Detection in 3D Point Clouds
Toan Nguyen, Minh Nhat Vu, Baoru Huang +6
Affordance detection and pose estimation are of great importance in many robotic applications. Their combination helps the robot gain an enhanced manipulation capability, in which…
Grasp-Anything: Large-scale Grasp Dataset from Foundation Models
An Dinh Vuong, Minh Nhat Vu, Hieu Le +5
Foundation models such as ChatGPT have made significant strides in robotic tasks due to their universal representation of real-world domains. In this paper, we leverage foundation…
Two-Step Online Trajectory Planning of a Quadcopter in Indoor Environments with Obstacles
Martin Zimmermann, Minh Nhat Vu, Florian Beck +2
This paper presents a two-step algorithm for online trajectory planning in indoor environments with unknown obstacles. In the first step, sampling-based path planning techniques su…