Masanori Aizawa

Learning Adaptive Policies for Autonomous Excavation Under Various Soil Conditions by Adversarial Domain Sampling

Excavation is a frequent task in construction. In this context, automation is expected to reduce hazard risks and labor-intensive work. To this end, recent studies have investigated using reinforcement learning (RL) to automate construction machines. One of the challenges in applying RL to excavatio