Navigation Task
Navigation tasks in robotics aim to enable robots to move efficiently and safely through various environments, often while completing specific objectives like object retrieval or reaching designated locations. Current research emphasizes robust navigation in complex, dynamic settings, incorporating social awareness, handling ambiguous instructions (often via large language models), and improving sample efficiency in reinforcement learning. These advancements are crucial for deploying robots in real-world scenarios, such as assistance in homes, warehouses, or disaster relief, and are driving innovation in areas like perception, planning, and control algorithms.
Papers
GenEx: Generating an Explorable World
Taiming Lu, Tianmin Shu, Junfei Xiao, Luoxin Ye, Jiahao Wang, Cheng Peng, Chen Wei, Daniel Khashabi, Rama Chellappa, Alan Yuille, Jieneng Chen
Towards Long-Horizon Vision-Language Navigation: Platform, Benchmark and Method
Xinshuai Song, Weixing Chen, Yang Liu, Weikai Chen, Guanbin Li, Liang Lin