Imitation Learning and Model Integrated Excavator Trajectory Planning
Qiangqiang Guo,Zhixian Ye,Liyang Wang,Liangjun Zhang,Qiangqiang Guo,Zhixian Ye,Liyang Wang,Liangjun Zhang
Automated excavation is promising to improve the safety and efficiency of excavators, and trajectory planning is one of the most important techniques. In this paper, we propose a two-stage method that integrates data-driven imitation learning and model-based trajectory optimization to generate optimal trajectories for autonomous excavators. We firstly train a deep neural network using demonstratio...
