A Model-Free Extremum-Seeking Approach to Autonomous Excavator Control Based on Output Power Maximization
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18-1073_01_MS.pdf
Description
Accepted version
Size
975.34 KB
Format
Adobe PDF
Checksum (MD5)
7397d8d56141a6bab2556abc68cca693
Author(s)
Sotiropoulos, Filippos Edward
Asada, Haruhiko
Date Issued
April 2019
Journal
IEEE Robotics and Automation Letters
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Sotiropoulos, Filippos E. and H. Harry Asada. "A Model-Free Extremum-Seeking Approach to Autonomous Excavator Control Based on Output Power Maximization." IEEE Robotics and Automation Letters 4, 2 (April 2019): 1005 - 1012 © 2019 IEEE
Version
Author's final manuscript
Abstract
A new approach to autonomous excavator control that allows the machine to adapt to unknown soil properties is presented. Unlike traditional force control or trajectory control, the new method uses the product of force and velocity, namely, the power transmitted from the excavator to the soil, as a signal for adaptive excavation. Using an extremum-seeking algorithm, an optimal excavation condition where the force and velocity at the bucket take a particular combination that maximizes the output power of the machine is sought and maintained. Under this condition, the system finds the optimal depth of digging by controlling the boom of the excavator. Also under this condition, the output impedance of the excavator matches the impedance of the load and, thereby, transmits the maximum power from the machine to the soil. Theoretical analysis proves that an optimal combination of force and velocity exists and is unique under mild assumptions. An extremum-seeking algorithm using recursive least squares is developed for maximizing the output power. The method is implemented on a small-scale prototype system where torque motors emulate nonlinear force-speed characteristics of hydraulic actuators. Experiments demonstrate that the prototype can execute excavation tasks adaptively against varying soil properties and terrain profile.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
d'Arbeloff Lab for Information Sytems and Technology (Massachusetts Institute of Technology)
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.1109/lra.2019.2893690
