Long Horizon Navigation

Long-horizon navigation focuses on enabling robots and autonomous vehicles to navigate complex environments over extended distances and time periods, often without relying on pre-existing maps. Current research emphasizes the integration of various techniques, including large language models (LLMs) for high-level planning and reasoning, transformer-based architectures for processing visual and temporal information, and reinforcement learning for adapting to dynamic environments. These advancements are crucial for improving the robustness and reliability of autonomous systems in diverse real-world applications, such as autonomous driving, exploration, and search and rescue.