Spatial Planning

Spatial planning encompasses the design and optimization of actions within physical spaces, aiming to achieve specific goals efficiently and safely. Current research heavily emphasizes online planning algorithms, particularly those leveraging reinforcement learning, Bayesian methods, and graph neural networks, to address challenges in partially observable environments and complex tasks like robot navigation and manipulation. These advancements are improving the efficiency and robustness of autonomous systems across diverse applications, from robotics and urban design to power grid management and disaster response. The development of comprehensive benchmarks and the integration of human insights are also key focuses, ensuring the reliability and practical applicability of these planning methods.