Date of Graduation

8-2022

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Engineering (PhD)

Degree Level

Graduate

Department

Industrial Engineering

Advisor/Mentor

Sarah G. Nurre Pinkley

Committee Member

Raymond R. Hill

Second Committee Member

Edward A. Pohl

Third Committee Member

Manuel D. Rossetti

Keywords

on-orbit servicing, scheduling, space robots

Abstract

This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to mathematically represent the movement of the tasks and refuelling depots and present algorithms for constructing both sets of data. We create robust case studies based on current operational satellites in Low Earth Orbit, Mid Earth Orbit, and Geosynchronous Earth Orbit. With these case studies we perform extensive computational experiments to present example insights about robot servicers, task completion, and their use of refuelling depots.

Building upon this work, we next focus on proving the computational complexity and generating fast, accurate algorithms and present and demonstrate two solution methods. The solution methods use node labels akin to those in Dijkstra's algorithm but include much more information about the servicers, tasks, and fuel levels. We use the labels to find the shortest paths to tasks which are in motion on the network. The first heuristic assigns servicers to tasks greedily and the second heuristic assigns tasks using a clustering algorithm. We use a case study to compare our heuristic time and solution performance with CPLEX with promising results.

In our final work, we address the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots with Known Task Times. Previously, we considered the tasks to have instantaneous completion which is realistic for surveillance type tasks but not for the more intricate tasks, such as corrective maintenance or equipment upgrade. Thus we remove the assumption of instantaneous task completion and consider a known task processing time. We present a new mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish the on-orbit servicing tasks. As both tasks and servicers move, considering task duration is complex because (i) the task and servicer must coincide at the correct location and time, (ii) the task and servicer must move through the network together for at least the duration of the processing time, and (iii) the completion of the task is at a different location and time than the start. The model accounts for the movement of the servicers, tasks, and refuelling depots and also for the task duration. We also present two related constructive heuristics for solving the problem. We also incorporate the task times into a case study which is based on satellites and orbits which are in use today. We use the case study to conduct computational experiments comparing the heuristic solving times and solution accuracy with CPLEX.

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