Excavation of Fragmented Rocks with Multi-modal Model-based Reinforcement Learning
Yifan Zhu,Liyang Wang,Liangjun Zhang,Yifan Zhu,Liyang Wang,Liangjun Zhang
This paper presents a multi-modal model-based reinforcement learning (MBRL) approach to the excavation of fragmented rocks, which are very challenging to model due to their highly variable sizes and geometries, and visual occlusions. A multi-modal recurrent neural network (RNN) learns the dynamics of bucket-terrain interaction from a small physical dataset, with a discrete set of motion primitives...
