Optimization techniques in science planning for planetary exploration missions
(English) Solar System robotic missions explore objects in space to elicit key information that contributes to our understanding of the origins and evolution of the Solar System as well as of life. Noticeably, such an ambitious purpose demands an equally challenging endeavor from the scientific and...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/692714 |
| Acceso en línea: | http://hdl.handle.net/10803/692714 https://dx.doi.org/10.5821/dissertation-2117-420573 |
| Access Level: | acceso abierto |
| Palabra clave: | Àrees temàtiques de la UPC::Aeronàutica i espai 629 |
| Sumario: | (English) Solar System robotic missions explore objects in space to elicit key information that contributes to our understanding of the origins and evolution of the Solar System as well as of life. Noticeably, such an ambitious purpose demands an equally challenging endeavor from the scientific and engineering perspectives—an effort that compels to procure high scientific revenues. In this context, science planning plays a key part to guarantee that the mission obtains as large an information harvest as possible to ultimately fulfill a set of scientific objectives. This list of mission objectives can be very extensive and diverse; from the search for life to the identification of planetary resources or the geomorphological analysis, many disciplines come together in this quest. To meet these objectives, spacecraft are equipped with a varied suite of instruments capable of conducting a wide range of experiments. Thorough planning is required to conciliate the instruments' operations while concurrently guaranteeing the spacecraft performance and safety, ensuring a good management of the available resources, as well as the feasibility to forward this information to Earth. These requirements and constraints often result in trade-offs among spacecraft subsystems, including the payload. All in all, the activity plan of a mission constitutes a complex problem that needs to account for a wide spectrum of agents in order to draw a suitable mission program that effectively fulfills the scientific objectives. Within this context, observation and mission planning software tools have played an important role in space missions—and their relevance is only expected to grow in the near future. From designing the instrumental observational activities to overall management of spacecraft resources and activity scheduling, various software tools have greatly assisted in the planning process of missions like Cassini, Dawn or Rosetta. Drawing upon these, this work presents the development and validation of a software prototype designed to streamline science planning processes for planetary exploration missions. Our study focuses on devising an optimized activity plan for a camera instrument, aiming to maximize its scientific return while ensuring efficient mission operations. This software prototype tool, named Observation Planning Tool for Instrument and Mission Analysis (OPTIMA), consists of two consecutive stages. The first one utilizes spacecraft trajectory and, possibly, attitude data to identify feasible observational opportunities based on geometric constraints derived from instrument measurement requirements. These opportunities, defined as science opportunity windows, are used to constrain the exploration space in the subsequent stage. The second phase applies optimization heuristics to develop potential activity plans that maximize scientific returns while adhering to both geometric and operational constraints. The tool's modularity allows for the application of various optimization heuristics tailored to the specific problem. Additionally, OPTIMA includes a component for simulating the camera's observation through mosaic heuristics that aim to achieve maximum coverage of Regions of Interest (ROIs) with minimal make-span. Finally, the methodology's efficacy is demonstrated through hypothetical case studies set in realistic mission scenarios, including a validation case study on Galileo's flybys over Europa and two others during different phases of the JUICE mission. These cases focus on optimizing coverage and/or resolution across various ROIs, considering additional adjustments such as downlink windows allocation and data compression. The algorithm successfully identifies nearly-optimal activity plans that comply with the specified constraints in all cases, showcasing the tool's efficiency and adaptability across different mission scenarios. This makes OPTIMA a valuable asset for multi-mission science planning in planetary exploration. |
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