A Data-Driven Approach to Prediction and Optimal Bucket-Filling Control for Autonomous Excavators

We develop a data-driven, statistical control method for autonomous excavators. Interactions between soil and an excavator bucket are highly complex and nonlinear, making traditional physical modeling difficult to use for real-time control. Here, we propose a data-driven method, exploiting data obta...

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Bibliographic Details
Main Authors: Sandzimier, Ryan Joseph., Asada, Haruhiko
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2020
Online Access:https://hdl.handle.net/1721.1/128006