2026-09-18T23:18:42Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1202262022-01-13T07:54:05Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Harry H. Asada.
Sotiropoulos, Filippos Edward
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2019-02-05T15:59:16Z
2019-02-05T15:59:16Z
2018
2018
http://hdl.handle.net/1721.1/120226
1083115097
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 45-46).
In this work an algorithm for controlling the motion of an autonomous excavator arm during excavation is presented. To deal with the challenge, posed by modeling and planning trajectories through soil, a model-free method is proposed which aims at maximally harnessing the capabilities of the excavator by matching its internal characteristics to those of the environment. By maximizing the power output of specific actuators the machine is able to strike a balance between disadvantageous operating conditions where it is either getting stuck in the soil or simply not utilizing its full potential to move soil towards task oriented goals. The real-time optimization, which used methods from extremum seeking control, was implemented in simulation and then on a small scale simulation rig which validated the method. It was shown that power maximization as a strategy of trajectory adaptation for excavation was both well-grounded and feasible.
by Filippos Edward Sotiropoulos.
S.M.
46 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Real-time trajectory optimization for excavators by power maximization
Thesis
application/pdf
Publication
unknown
unknown
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<Abstract>In this work an algorithm for controlling the motion of an autonomous excavator arm during excavation is presented. To deal with the challenge, posed by modeling and planning trajectories through soil, a model-free method is proposed which aims at maximally harnessing the capabilities of the excavator by matching its internal characteristics to those of the environment. By maximizing the power output of specific actuators the machine is able to strike a balance between disadvantageous operating conditions where it is either getting stuck in the soil or simply not utilizing its full potential to move soil towards task oriented goals. The real-time optimization, which used methods from extremum seeking control, was implemented in simulation and then on a small scale simulation rig which validated the method. It was shown that power maximization as a strategy of trajectory adaptation for excavation was both well-grounded and feasible.</Abstract>
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