8 papers
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…
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…
SR-SLAM: Scene-reliability Based RGB-D SLAM in Diverse Environments
Haolan Zhang, Chenghao Li, Thanh Nguyen Canh +2
Visual simultaneous localization and mapping (SLAM) plays a critical role in autonomous robotic systems, especially where accurate and reliable measurements are essential for navig…
Adaptive Prior Scene-Object SLAM for Dynamic Environments
Haolan Zhang, Thanh Nguyen Canh, Chenghao Li +1
Visual Simultaneous Localization and Mapping (SLAM) plays a vital role in real-time localization for autonomous systems. However, traditional SLAM methods, which assume a static en…
Quality-focused Active Adversarial Policy for Safe Grasping in Human-Robot Interaction
Chenghao Li, Razvan Beuran, Nak Young Chong
Vision-guided robot grasping methods based on Deep Neural Networks (DNNs) have achieved remarkable success in handling unknown objects, attributable to their powerful generalizabil…
Learning to Negotiate via Voluntary Commitment
Shuhui Zhu, Baoxiang Wang, Sriram Ganapathi Subramanian +1
The partial alignment and conflict of autonomous agents lead to mixed-motive scenarios in many real-world applications. However, agents may fail to cooperate in practice even when…