المؤلفون: Ho, Koki, Shimane, Yuri, Isaji, Masafumi

مصطلحات موضوعية: Mathematics - Optimization and Control

الوصف: Recent growing complexity in space missions has led to an active research field of space logistics and mission design. This research field leverages the key ideas and methods used to handle complex terrestrial logistics to tackle space logistics design problems. A typical goal in space logistics is to optimize the commodity flow to satisfy some mission objectives with the lowest cost. One of the successful space logistics approaches is network flow modeling and optimization using mixed-integer linear programming (MILP). A caveat of the conventional MILP-based network approach for space logistics is its incapability of handling nonlinearity. For example, in the MILP formulation, the spacecraft structure mass and fuel/payload capacity are approximated by a linear relationship. However, this oversimplified relationship cannot characterize a realistic spacecraft design. Other types of nonlinearity can appear when a nonlinear time-dependent trajectory model is considered in an event-driven network, where the time step of each event itself is a variable. In response to this challenge, this Note develops a new systematic general framework to handle nonlinearity in the MILP-based space logistics formulation using machine learning (ML). Specifically, we replace the nonlinear constraints in the space logistics formulation with trained ML models that are compatible with MILP. The MILP-compatible ML model includes linear regression, PWL approximations, neural networks (NN) with Rectified Linear Unit (ReLU) activations, decision tree regression, and random forest regression, among others; these models can be translated into MILP formulations with a definition of additional variables and constraints while maintaining the linearity. This Note provides the first demonstration of using such trained ML models directly in a MILP-based space logistics optimization formulation.
Comment: 12 pages, 2 figures, under review by AIAA Journal of Spacecraft and Rockets

الوصول الحر: http://arxiv.org/abs/2404.18770Test

المؤلفون: Nolton, Isabel, Tomita, Kento, Shimane, Yuri, Ho, Koki

مصطلحات موضوعية: Nonlinear Sciences - Chaotic Dynamics, Mathematics - Optimization and Control

الوصف: This study analyzes the sensitivity of the dynamics around Weak Stability Boundary Transfers (WSBT) in the elliptical restricted three-body problem. With WSBTs increasing popularity for cislunar transfers, understanding its inherently chaotic dynamics becomes pivotal for guiding and navigating cooperative spacecrafts as well as detecting non-cooperative objects. We introduce the notion of separation time to gauge the deviation of a point near a nominal WSBT from the trajectory's vicinity. Employing the Cauchy-Green tensor to identify stretching directions in position and velocity, the separation time, along with the Finite-Time Lyapunov Exponent are studied within a ball of state uncertainty scaled to typical orbit determination performances.
Comment: 18 pages, 13 figures, This paper was presented at the AAS/AAIA astrodynamics specialist conference, August 13-17, 2023, Big Sky, MT, USA

الوصول الحر: http://arxiv.org/abs/2402.00717Test

المؤلفون: Lee, Hang Woon, Rogers, David O. Williams, Pearl, Brycen D., Chen, Hao, Ho, Koki

مصطلحات موضوعية: Mathematics - Optimization and Control, Electrical Engineering and Systems Science - Systems and Control

الوصف: In this paper, we address the problem of reconfiguring Earth observation satellite constellation systems through multiple stages. The Multi-stage Constellation Reconfiguration Problem (MCRP) aims to maximize the total observation rewards obtained by covering a set of targets of interest through the active manipulation of the orbits and relative phasing of constituent satellites. In this paper, we consider deterministic problem settings in which the targets of interest are known a priori. We propose a novel integer linear programming formulation for MCRP, capable of obtaining provably optimal solutions. To overcome computational intractability due to the combinatorial explosion in solving large-scale instances, we introduce two computationally efficient sequential decision-making methods based on the principles of a myopic policy and a rolling horizon procedure. The computational experiments demonstrate that the devised sequential decision-making approaches yield high-quality solutions with improved computational efficiency over the baseline MCRP. Finally, a case study using Hurricane Harvey data showcases the advantages of multi-stage constellation reconfiguration over single-stage and no-reconfiguration scenarios.
Comment: 39 pages, 13 figures, submitted to the Journal of Spacecraft and Rockets

الوصول الحر: http://arxiv.org/abs/2401.11567Test

المؤلفون: Patel, Malav, Shimane, Yuri, Lee, Hang Woon, Ho, Koki

مصطلحات موضوعية: Mathematics - Optimization and Control

الوصف: Cislunar space awareness is of increasing interest to the international community as Earth-Moon traffic is projected to increase. This raises the problem of placing satellites optimally in a constellation to provide satisfactory coverage for said traffic. The Circular Restricted 3 Body Problem (CR3BP) provides promising periodic orbits in the Earth-Moon rotating frame for traffic monitoring. This work converts a spatially and temporally varying traffic coverage requirement into an integer linear programming problem, attempting to minimize the number of satellites required for the requested coverage.
Comment: 18 pages, 15 figures, submitted to 2023 AAS Conference

الوصول الحر: http://arxiv.org/abs/2311.10252Test

المؤلفون: Tomita, Kento, Shimane, Yuri, Ho, Koki

مصطلحات موضوعية: Electrical Engineering and Systems Science - Systems and Control

الوصف: This paper delves into the predictive sensor tasking algorithm for the multi-observer, multi-target sensor setting, leveraging the Extended Information Filter (EIF). Conventional predictive formulations suffer from the curse of dimensionality due to the dependence of the performance metric on the target-observer assignment history. This paper exploits the EIF's additive structure of measurement information to break the dependence and devises an efficient linear integer programming formulation. We further investigate the resulting formulation to study how the cislunar dynamics expands and shrinks the measurement information, and discuss when the information gain is maximized in relation to the observation space and the uncertainty deformation caused by the dynamics. We numerically demonstrate that the predictive sensor tasking algorithm outperforms the myopic algorithm in two different metrics, depending on the formulation.

الوصول الحر: http://arxiv.org/abs/2310.04894Test

المؤلفون: Gollins, Nicholas, Ho, Koki

مصطلحات موضوعية: Mathematics - Optimization and Control

الوصف: Space exploration plans are becoming increasingly complex as public agencies and private companies target deep-space locations, such as cislunar space and beyond, which require long-duration missions and many supporting systems and payloads. Optimizing multi-mission exploration campaigns is challenging due to the large number of required launches as well as their sequencing and compatibility requirements, making the conventional space logistics formulations not scalable. To tackle this challenge, this paper proposes an alternative approach that leverages a two-level hierarchical optimization algorithm: a genetic algorithm is used to explore the campaign scheduling solution space, and each of the solutions is then evaluated using a time-expanded multi-commodity flow mixed-integer linear program. A number of case studies, focusing on the Artemis lunar exploration program, demonstrate how the method can be used to analyze potential campaign architectures. The method enables a potential mission planner to study the sensitivity of a campaign to program-level parameters such as logistics vehicle availability and performance, payload launch windows, and in-situ resource utilization infrastructure efficiency.
Comment: 47 pages, 12 figures, submitted to Journal of Spacecraft and Rockets

الوصول الحر: http://arxiv.org/abs/2308.00632Test

المؤلفون: Ho, Koki

مصطلحات موضوعية: Mathematics - Optimization and Control

الوصف: As "Space Mobility and Logistics" was listed as one of the five core competencies in the US Space Force's doctrine document, there is a growing interest in developing technologies to enable in-space refueling, servicing, assembly, and manufacturing as well as other in-space logistics operations. Modeling for space mobility and logistics requires a new approach that differs from conventional astrodynamics because it needs to consider the coordination of multiple vehicles to satisfy an overall demand; namely, the optimal trajectory of one vehicle does not necessarily lead to the optimal campaign solution that contains multiple vehicles and infrastructure elements. In addition, for in-space servicing applications, we need additional analysis capabilities to analyze and optimize the sizes of the fuel/spare depots and their inventory/sparing policies with orbital mechanics in mind. To tackle these challenges, there have been various attempts to leverage terrestrial logistics-driven techniques, coupled with astrodynamics, to enhance in-space operations. This paper aims to provide a review of the literature by categorizing the state-of-the-art studies in two ways: (1) by application questions that are addressed; and (2) by logistics-driven methods that are used in the studies. The two categorizations are expected to help both practitioners and researchers understand the state of the art and identify the under-explored and promising future research directions.
Comment: Presented at AIAA SciTech Conference 2024; Submitted to the AIAA Journal of Spacecraft and Rockets

الوصول الحر: http://arxiv.org/abs/2306.01107Test

المؤلفون: Tomita, Kento, Ho, Koki

مصطلحات موضوعية: Computer Science - Robotics

الوصف: Autonomous hazard detection and avoidance is a key technology for future landing missions in unknown surface conditions. Current state-of-the-art stochastic algorithms assume simple Gaussian measurement noise on dense, high-fidelity digital elevation maps, limiting the algorithm's applicability. This paper introduces a new stochastic hazard detection algorithm capable of more general topographic uncertainty by leveraging the Gaussian random field regression. The proposed approach enables the safety assessment with imperfect and sparse sensor measurements, which allows hazard detection operations under more diverse conditions. We demonstrate the performance of the proposed approach on the existing Mars digital terrain models.

الوصول الحر: http://arxiv.org/abs/2305.04249Test

المؤلفون: Ikeya, Kosuke, Ho, Koki

مصطلحات موضوعية: Mathematics - Optimization and Control

الوصف: As many satellite constellations are proposed, deployed, and operated, their maintenance becomes increasingly important to provide satisfactory services; therefore, on-orbit refueling to spacecraft has become one of the most promising technologies for realizing more sustainable space development. This paper develops an analytical model to examine two types of mission architectures for multi-target on-orbit refueling missions: a non-cooperative architecture and a cooperative architecture. In the (rather conventional) non-cooperative refueling architecture, a servicer spacecraft visits passive targets one by one, whereas, in the cooperative refueling architecture, both the servicer and the targets can actively maneuver to complete refueling cooperatively. This paper analytically compares the fuel mass required in each architecture to support the decision-making process of mission architects. Furthermore, the condition under which the cooperative architecture becomes more efficient than the non-cooperative architecture is analytically derived. The sensitivities of this condition against key mission parameters, such as the number of targets and their inclination, are also analyzed through a case study of multi-plane multi-target on-orbit refueling in low Earth orbits.
Comment: 22 pages, 12 figures, under review by the AIAA Journal of Spacecraft and Rockets

الوصول الحر: http://arxiv.org/abs/2302.14563Test

المؤلفون: Jo, Byeong-Un, Ho, Koki

مصطلحات موضوعية: Mathematics - Optimization and Control

الوصف: A sizing procedure for a rocket family capable of fulfilling multiple missions considering the commonality is presented. The procedure aims to take full advantage of sharing a common part across multiple rockets whose payload capability differs entirely, ultimately leading to cost savings in designing a rocket family. As the foundation of the proposed rocket family design method, an integrated sizing method with trajectory optimization for a single rocket is first formulated as a single optimal control problem. This formulation can find the optimal sizing along with trajectory results in a tractable manner. Building upon this formulation, the proposed rocket family design method is developed to (1) determine the feasible design space of the rocket family design problem (i.e., commonality check); and (2) if a feasible design space is determined to exist, minimize the cost function within that feasible space by solving an optimization problem in which the optimal control problem is embedded as subproblems. A case study is carried out on a rocket family composed of expendable and reusable launchers to demonstrate the novelty of the proposed procedure.
Comment: 24 pages, 7 figures, under review by the AIAA Journal of Spacecraft and Rockets

الوصول الحر: http://arxiv.org/abs/2302.12900Test