{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/120226"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/120226","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Real-time trajectory optimization for excavators by power maximization","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_html":"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_has_math":false,"creators":["Sotiropoulos, Filippos Edward"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Mechanical Engineering.","school":null,"contributors":[],"advisors":["Harry H. 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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."],"dc:description.degree":["S.M."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/120226"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["MIT theses are protected by copyright. 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