Dynamic Modeling, Simulation, and Analysis of Orbiting Sample Capture for Potential Mars Sample Return

Ishigo, Alyssa; Marteau, E.; Ohta, Preston; Elliott, Ethan; Younse, Paulo

doi:10.1109/aero47225.2020.9172438

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…Extensive modeling and simulation were performed to verify that the architecture could meet its functional and performance requirements while keeping within system technical constraints. This included simulations to verify OS capture performance, optimize capture trigger sensor configurations, characterize OS‐spacecraft interactions, assess vision‐based pose‐estimation and surface inspection of the OS, estimate operation time, evaluate kinematics of the capture lid and linear transfer mechanism end effector, and estimate power draw and data volume generation 2,4,5 . Modeling and simulation were instrumental in developing, characterizing, verifying, and validating the COM architecture, as well as facilitating infusion of key technologies into the final MSR Mission Concept Review (MCR) baseline system architecture.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of model‐based and traditional systems engineering approaches for simulating a robotic space system architecture through automatic knowledge processing

Younse

Cameron

Bradley

2022

Systems Engineering

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Model-based Systems Engineering (MBSE) case studies in the literature assert that there are benefits to MBSE when applied to modeling and simulating space systems. This research evaluates the benefits of an MBSE modeling and simulation approach over a traditional, non-MBSE approach through modeling and simulation of an orbiting sample Capture and Orient Module (COM) architecture for potential Mars Sample Return (MSR). The COM architecture was modeled, simulated, and evaluated against nominal load power and output data rate requirements to compare the two approaches. A new modeling and simulation-centric V-model was synthesized from existing V-model and modeling and simulation process models to map out the modeling and simulation activities within the context of the system development lifecycle and used as a tool to compare the non-MBSE and MBSE approaches. A three-phase modeling and simulation process consisting of an analysis and modeling phase, computer programming and implementation phase, and experimentation phase was used to model and simulate the COM. The total number of manual and automatic knowledge processed was calculated for both approaches and used to quantify the benefits of the MBSE approach relative to the non-MBSE approach. In the non-MBSE approach, all knowledge elements were manually processed during the modeling and simulation process. In the MBSE approach, 49% of total knowledge processing was automated.The MBSE approach showed user experience benefits with modeling and simulating the COM robotic space system through providing a higher level of support for automation, reducing the burden of systems engineering tasks, and reducing effort.

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Section: Introductionmentioning

confidence: 99%

Comparative analysis of model‐based and traditional systems engineering approaches for simulating a robotic space system architecture through automatic knowledge processing

Younse

Cameron

Bradley

2022

Systems Engineering

Self Cite

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Concept for an On-orbit Capture and Orient Module for Potential Mars Sample Return

Younse

Chiu

Cameron

et al. 2020

2020 IEEE Aerospace Conference

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A High-Reliability Photoelectric Detection System for Mars Sample Return’s Orbiting Sample

Church,

Guzman-Garcia,

Bertelsmann

et al. 2024

Aerospace

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The Mars Sample Return campaign is an endeavor of unprecedented technological complexity and coordination that attempts to answer fundamental questions about the habitability of Mars by returning the first samples of Martian material to Earth for analysis. The third mission in the campaign consists of the NASA-provided Capture, Containment, and Return System (CCRS) onboard the European Space Agency’s Earth Return Orbiter, which will retrieve the Orbiting Sample (OS) container from its orbit around Mars. Retrieving a passive sample container from a planetary orbit has never been attempted by any spacecraft and requires the development of new technology to succeed in this ambitious task. This paper introduces the high-reliability Capture Sensor Suite (CSS), a novel optical detection system that provides CCRS with the capability to autonomously detect the OS as it is captured. This article will discuss the challenges and requirements for the fault-tolerant design of the CSS.

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Dynamic Modeling, Simulation, and Analysis of Orbiting Sample Capture for Potential Mars Sample Return

Cited by 3 publications

References 5 publications

Comparative analysis of model‐based and traditional systems engineering approaches for simulating a robotic space system architecture through automatic knowledge processing

Comparative analysis of model‐based and traditional systems engineering approaches for simulating a robotic space system architecture through automatic knowledge processing

Concept for an On-orbit Capture and Orient Module for Potential Mars Sample Return

A High-Reliability Photoelectric Detection System for Mars Sample Return’s Orbiting Sample

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