Navigation Skill

Navigation skill in robotics and AI focuses on enabling agents to efficiently and effectively reach goals within various environments, guided by instructions or learned objectives. Current research emphasizes developing robust and adaptable navigation systems using reinforcement learning, large language models (LLMs), and biologically-inspired approaches like active inference, often incorporating multimodal data fusion (e.g., vision and language) and advanced planning techniques. These advancements are crucial for improving autonomous systems in diverse applications, from mobile robots and autonomous vehicles to virtual agents, and contribute to a deeper understanding of both artificial and biological navigation strategies.