ExACT: An End-to-End Autonomous Excavator System Using Action Chunking With Transformers

arXiv:2405.05861v1 Announce Type: cross
Abstract: Excavators are crucial for diverse tasks such as construction and mining, while autonomous excavator systems enhance safety and efficiency, address labor shortages, and improve human working conditions. Different from the existing modularized approaches, this paper introduces ExACT, an end-to-end autonomous excavator system that processes raw LiDAR, camera data, and joint positions to control excavator valves directly. Utilizing the Action Chunking with Transformers (ACT) architecture, ExACT employs imitation learning to take observations from multi-modal sensors as …

arxiv autonomous cs.ai cs.lg cs.ro transformers type