Geometric Navigation

Geometric navigation in robotics aims to enable autonomous agents to efficiently and safely traverse complex environments. Current research emphasizes hybrid approaches that integrate geometric planning methods, leveraging established strengths in handling structured obstacles, with learning-based techniques, particularly deep learning models, to incorporate semantic understanding of terrain and social contexts. This fusion addresses limitations of purely geometric or purely learned systems, improving robustness, adaptability, and performance in diverse, unstructured settings. Such advancements are crucial for deploying robots in real-world scenarios, ranging from warehouse automation to outdoor exploration and human-robot interaction.