Human Navigation

Human navigation research aims to understand and replicate human-like navigation in robots and AI agents, focusing on efficient and socially compliant movement in complex environments. Current research emphasizes the development of models that integrate visual and linguistic instructions, learn from human demonstrations (using techniques like imitation and reinforcement learning), and incorporate spatial reasoning and memory. This work is significant for advancing robotics, autonomous systems, and human-computer interaction, leading to improved robot navigation in real-world settings and a deeper understanding of human spatial cognition.