1 citations · 1 across the 13 of their papers we have counts for
14 papers
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…
Probe-to-Grasp Manipulation Using Self-Sensing Pneumatic Variable-Stiffness Joints
Ngoc Duy Tran, Yeman Fan, Feng Dai +5
Grasping deformable objects with varying stiffness remains a significant challenge in robotics. Estimating the local stiffness of a target object is important for determining an op…
Soft Rigid Hybrid Gripper with Inflatable Silicone Pockets for Tunable Frictional Grasping
Hoang Hiep Ly, Cong-Nhat Nguyen, Doan-Quang Tran +6
Grasping objects with diverse mechanical properties, such as heavy, slippery, or fragile items, remains a significant challenge in robotics. Conventional rigid grippers typically r…
MDToC: Metacognitive Dynamic Tree of Concepts for Boosting Mathematical Problem-Solving of Large Language Models
Tung Duong Ta, Tim Oates, Thien Van Luong +2
Despite advances in mathematical reasoning capabilities, Large Language Models (LLMs) still struggle with calculation verification when using established prompting techniques. We p…
CADKnitter: Compositional CAD Generation from Text and Geometry Guidance
Tri Le, Khang Nguyen, Baoru Huang +2
Computer-aided design (CAD) defines 3D models as compact, precise, and editable representations, making it directly useful for several fields. Recently, CAD generation has been gai…
Hybrid Gripper Finger Enabling In-Grasp Friction Modulation Using Inflatable Silicone Pockets
Hoang Hiep Ly, Cong-Nhat Nguyen, Doan-Quang Tran +6
Grasping objects with diverse mechanical properties, such as heavy, slippery, or fragile items, remains a significant challenge in robotics. Conventional grippers often rely on app…
MobiDock: Design and Control of A Modular Self Reconfigurable Bimanual Mobile Manipulator via Robotic Docking
Xuan-Thuan Nguyen, Khac Nam Nguyen, Ngoc Duy Tran +4
Multi-robot systems, particularly mobile manipulators, face challenges in control coordination and dynamic stability when working together. To address this issue, this study propos…
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…
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…
SplineFormer: An Explainable Transformer-Based Approach for Autonomous Endovascular Navigation
Tudor Jianu, Shayan Doust, Mengyun Li +8
Endovascular navigation is a crucial aspect of minimally invasive procedures, where precise control of curvilinear instruments like guidewires is critical for successful interventi…
Hybrid Gripper with Passive Pneumatic Soft Joints for Grasping Deformable Thin Objects
Ngoc-Duy Tran, Hoang-Hiep Ly, Xuan-Thuan Nguyen +3
Grasping a variety of objects remains a key challenge in the development of versatile robotic systems. The human hand is remarkably dexterous, capable of grasping and manipulating…
Single Actuator Undulation Soft-bodied Robots Using A Precompressed Variable Thickness Flexible Beam
Tung D. Ta
Soft robots - due to their intrinsic flexibility of the body - can adaptively navigate unstructured environments. One of the most popular locomotion gaits that has been implemented…
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…