Tat Hieu Bui — accepted AI-conference papers

2024

CoAS-Net: Context-Aware Suction Network With a Large-Scale Domain Randomized Synthetic Dataset

Yeong Gwang Son, Tat Hieu Bui, Ju Yong Hong, Yong Hyeon Kim, Seung Jae Moon, Chun Soo Kim +3

RA-L 2024

Robotic grasping is one of the essential skills in robotics. From industrial to housework, robots are required to handle objects, enabling them to interact with their surroundings. Among the various tasks in robotic grasping, bin-picking is considered one of the most challenging because of the clutt

Cited by 6 Source ↗Scholar ↗

2023

Deep Learning Based 6-DoF Antipodal Grasp Planning From Point Cloud in Random Bin-Picking Task Using Single-View

Tat Hieu Bui, Yeong Gwang Son, Seung Jae Moon, Quang Huy Nguyen, Issac Rhee, Ju Yong Hong +1

RA-L 2023

Random bin picking is a crucial task in logistic centers, which is driven by E-Commerce growth. In this letter, we present an end-to-end method for 6-DoF antipodal grasps from cluttered scenes. Our approach includes two main steps: finding Potential Grasp Areas (PGAs) from depth image of the bin and

Cited by 9 Source ↗Scholar ↗