Learning Excavation

Learning excavation focuses on developing autonomous systems capable of efficiently and effectively removing material from various terrains and environments. Current research emphasizes improving excavation strategies through reinforcement learning, incorporating oscillatory motions and adaptive impedance control to handle challenging materials and terrains, and developing robust planning systems that integrate global and local path planning for optimal excavation sequences. These advancements are significant for improving efficiency and safety in construction, mining, and other earth-moving applications, particularly by reducing reliance on human operators in hazardous or unpredictable conditions.