Object Navigation

Object navigation research focuses on enabling robots to autonomously navigate to specified objects within unseen environments, primarily using visual input and often incorporating natural language instructions. Current efforts concentrate on improving robustness and efficiency through various approaches, including large vision-language models (LVLMs), graph neural networks for reasoning about object relationships, and modular architectures that combine exploration and exploitation strategies. These advancements are crucial for developing more capable robots for applications ranging from household assistance to industrial automation, driving progress in embodied AI and robotics.