5 papers
FSUNav: A Cerebrum-Cerebellum Architecture for Fast, Safe, and Universal Zero-Shot Goal-Oriented Navigation
Mingao Tan, Yiyang Li, Shanze Wang +2
Current vision-language navigation methods face substantial bottlenecks regarding heterogeneous robot compatibility, real-time performance, and navigation safety. Furthermore, they…
CeRLP: A Cross-embodiment Robot Local Planning Framework for Visual Navigation
Haoyu Xi, Mingao Tan, Xinming Zhang +5
Visual navigation for cross-embodiment robots is challenging due to variations in robot and camera configurations, which can lead to the failure of navigation tasks. Previous appro…
MAER-Nav: Bidirectional Motion Learning Through Mirror-Augmented Experience Replay for Robot Navigation
Shanze Wang, Mingao Tan, Zhibo Yang +4
Deep Reinforcement Learning (DRL) based navigation methods have demonstrated promising results for mobile robots, but suffer from limited action flexibility in confined spaces. Con…
Enhancing Deep Reinforcement Learning-based Robot Navigation Generalization through Scenario Augmentation
Shanze Wang, Mingao Tan, Zhibo Yang +4
This work focuses on enhancing the generalization performance of deep reinforcement learning-based robot navigation in unseen environments. We present a novel data augmentation app…
Beyond Visibility Limits: A DRL-Based Navigation Strategy for Unexpected Obstacles
Mingao Tan, Shanze Wang, Biao Huang +4
Distance-based reward mechanisms in deep reinforcement learning (DRL) navigation systems suffer from critical safety limitations in dynamic environments, frequently resulting in co…