9 papers
Decoupled Object-Centric Video Understanding for Generating Robotic Manipulation Commands
Thanh Nguyen Canh, Thanh-Tuan Tran, Haolan Zhang +3
Translating video demonstrations into executable robot commands remains challenging because existing methods often fail to identify which objects are functionally involved in the d…
BPDA-GMM: Bayesian Probabilistic Data Association via Gaussian Mixture Models for Semantic SLAM
Thanh Nguyen Canh, Haolan Zhang, Xiem HoangVan +2
Probabilistic data association (PDA) improves semantic SLAM in perceptually aliased scenes, but existing methods often assume a fixed landmark set, recompute association weights as…
Multimodal Adversarial Quality Policy for Safe Grasping
Kunlin Xie, Chenghao Li, Haolan Zhang +1
Vision-guided robot grasping based on Deep Neural Networks (DNNs) generalizes well but poses safety risks in the Human-Robot Interaction (HRI). Recent works solved it by designing…
Human-to-Robot Interaction: Learning from Video Demonstration for Robot Imitation
Thanh Nguyen Canh, Thanh-Tuan Tran, Haolan Zhang +3
Learning from Demonstration (LfD) offers a promising paradigm for robot skill acquisition. Recent approaches attempt to extract manipulation commands directly from video demonstrat…
Semantic Visual Simultaneous Localization and Mapping: A Survey on State of the Art, Challenges, and Future Directions
Thanh Nguyen Canh, Haolan Zhang, Xiem HoangVan +1
Semantic Simultaneous Localization and Mapping (SLAM) is a critical area of research within robotics and computer vision, focusing on the simultaneous localization of robotic syste…
IL-SLAM: Intelligent Line-assisted SLAM Based on Feature Awareness for Dynamic Environments
Haolan Zhang, Thanh Nguyen Canh, Chenghao Li +3
Visual Simultaneous Localization and Mapping (SLAM) plays a crucial role in autonomous systems. Traditional SLAM methods, based on static environment assumptions, struggle to handl…