Publications
What could we do with a 20-meter tower on the Lunar South Pole? Applications of the Multifunctional Expandable Lunar Lite & Tall Tower (MELLTT)
November 16, 2020
Conference Paper
Published in:
ASCEND, virtual event, 16-18 November 2020.
Summary
Lunar polar regions and permanently shadowed regions (PSRs) are a key component of NASA's exploration objectives for the lunar surface, given their potential for a high abundance of volatiles like water. The Massachusetts Institute of Technology (MIT) Big Idea Challenge Team proposed the use of deployable towers to support robotic and remote exploration of these PSRs, alleviating limitations imposed by the rugged terrain. This deployable tower technology (called MELLTT) could enable an extended ecosystem on the lunar surface. This paper seeks to build on this initial concept by showcasing the advantages of self-deploying lightweight lunar towers through the development of various payload concepts. The payloads include 5-kg packages for an initial proof-of-concept deployment, as well as 50-kg payloads and payloads across multiple towers for future exploration architectures. The primary goal of a 5-kg tower payload is to return unique scientific data from a PSR while minimizing risk to a tower technology demonstration mission. Concepts include passive imagers to provide a step-change improvement in resolution, solar reflectors capable of illuminating PSRs, communications infrastructure for human and robotic exploration, a power beaming demonstration, and a PSR impactor. These payloads demonstrate the utility of towers on the lunar surface and how incremental improvements in the capability of towers can further NASA's exploration program.
Summary
Lunar polar regions and permanently shadowed regions (PSRs) are a key component of NASA's exploration objectives for the lunar surface, given their potential for a high abundance of volatiles like water. The Massachusetts Institute of Technology (MIT) Big Idea Challenge Team proposed the use of deployable towers to support robotic...
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Antennas and RF components designed with graded index composite materials
July 27, 2020
Conference Paper
Published in:
2020 Intnl. Applied Computational Electromagnetics Society Symp., ACES, 27-31 July 2020.
Summary
Antennas and RF components in general, can greatly benefit with the recent development of low-loss 3D print graded index materials. The additional degrees of freedom provided by graded index materials can result in the design of antennas and other RF components with superior performance than currently available designs based on conventional constant permittivity materials. Here we discuss our work designing flat lenses for antennas and RF matching networks as well as filters based on graded index composite materials.
Summary
Antennas and RF components in general, can greatly benefit with the recent development of low-loss 3D print graded index materials. The additional degrees of freedom provided by graded index materials can result in the design of antennas and other RF components with superior performance than currently available designs based on...
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Graded index dielectric superstrate for phased array scan compensation
July 5, 2020
Conference Paper
Published in:
2020 IEEE Intl. Symp. on Antennas and Propagation and North American Radio Science Meeting, 5-10 July 2020.
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Summary
This paper presents the use of additively manufactured graded index materials to improve the scan impedance variation of phased arrays. Solvent-based extrusion permits the programmatically controlled printing of chosen material properties with relative permittivity ranging from 2 to 24.5. This low-loss material shows promise for improvement of scan impedance variation for high scan angles in a smaller footprint than discrete layers.
Adjoint analysis of guidance systems for time-series inputs using Fourier analysis
July 1, 2020
Journal Article
Published in:
J. Guid., Control, Dyn., Vol. 43, No. 7, July 2020.
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Summary
The adjoint technique is a proven technique for analysis of linear time-varying systems and is widely used in the missile design community. It is a very efficient technique that can solve for both deterministic and stochastic disturbances and can develop a miss distance budget in a single computer solution of the differential equations without use of time-consuming Monte Carlo simulations. The adjoint technique is very valuable in both preliminary and more advanced missile design stages and is based upon the mathematical adjoint of the system dynamics matrix of the homing loop. Zarchan [1,2] describes extensive use of the technique for a variety of disturbances for homing missiles, and this author has developed its use for command guided missiles [3]. For adjoint analysis, the usual method of modeling maneuver disturbances to a missile guidance system starts by modeling the maneuver in the forward-time system as a delta function input into a transfer function with the same second-order statistics as the maneuver, and its output is input into the guidance system; then the system is converted into its adjoint system [1]. Bucco and Weiss [4] show that a set of nonstandard time-varying inputs cannot be treated in the normal fashion [2,5,6], and they present a new technique that enables these nonstandard inputs to be analyzed using adjoint analysis. This paper was inspired by and extends the results of the paper by Bucco and Weiss [4]. This paper shows that the use of the complex digital Fourier amplitude spectrums of both the maneuver and the adjoint impulse response at the maneuver point allows adjoint analysis to address another type of nonstandard input, namely, an arbitrary time-series inputs such as specific target maneuvers that are not representable by an impulse input into a transfer function; heretofore, these time-series inputs have not been treatable with adjoint analysis. Additionally, if there are several sets of arbitrary time series of target maneuvers, each with an associated probability of occurrence, the root-mean-square (rms) value of the set of probabilistic maneuvers can be calculated, another significant new capability introduced in this paper.
Summary
The adjoint technique is a proven technique for analysis of linear time-varying systems and is widely used in the missile design community. It is a very efficient technique that can solve for both deterministic and stochastic disturbances and can develop a miss distance budget in a single computer solution of...
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A hands-on middle-school robotics software program at MIT
March 28, 2020
Conference Paper
Published in:
IEEE Integrated STEM Education Conf., 28 March 2020.
Summary
Robotics competitions at the high school level attract a large number of students across the world. However, there is little emphasis on leveraging robotics to get middle school students excited about pursuing STEM education. In this paper, we describe a new program that targets middle school students in a local, four-week setting at the Massachusetts Institute of Technology (MIT). It aims to excite students by teaching the very basics of computer vision and robotics. The students program mini car-like robots, equipped with state-of-the-art computers, to navigate autonomously in a mock race track. We describe the hardware and software infrastructure that enables the program, the details of our curriculum, and the results of a short assessment. In addition, we describe four short programs, as well as a session where we teach high school teachers how to teach similar courses at their schools to their own students. The self-assessment indicates that the students feel more confident in programming and robotics after leaving the program, which we hope will enable them to pursue STEM education and robotics initiatives at school.
Summary
Robotics competitions at the high school level attract a large number of students across the world. However, there is little emphasis on leveraging robotics to get middle school students excited about pursuing STEM education. In this paper, we describe a new program that targets middle school students in a local...
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CW radar operation in the focused near-field
April 14, 2019
Conference Paper
Published in:
2019 Intl. Applied Computational Electromagnetics Society Symp., ACES, 14-19 April 2019.
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Summary
In this paper we will show by computer simulation and by measurements that the horn antennas of a bi-static radar operating in the near-field have a distinct maximum at a non-zero range. By focusing the antennas on this hot spot a low-powered, continuous-wave Ku-band radar could detect flying mosquitoes at very short range.
Simulation approach to sensor placement using Unity3D
September 25, 2018
Conference Paper
Published in:
IEEE High Performance Extreme Computing Conf., HPEC, 25-27 September 2018.
Summary
3D game simulation engines have demonstrated utility in the areas of training, scientific analysis, and knowledge solicitation. This paper will make the case for the use of 3D game simulation engines in the field of sensor placement optimization. Our study used a series of parallel simulations in the Unity3D simulation framework to answer the questions: how many sensors of various modalities are required and where they should be placed to meet a desired threat detection threshold? The result is a framework that not only answers this sensor placement question, but can be easily expanded to differing optimization criteria as well as answer how a particular configuration responds to differing crowd flows or informed/non-informed adversaries. Additionally, we demonstrate the scalability of this framework by running parallel instances on a supercomputing grid and illustrate the processing speed gained.
Summary
3D game simulation engines have demonstrated utility in the areas of training, scientific analysis, and knowledge solicitation. This paper will make the case for the use of 3D game simulation engines in the field of sensor placement optimization. Our study used a series of parallel simulations in the Unity3D simulation...
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Human-machine collaborative optimization via apprenticeship scheduling
September 1, 2018
Journal Article
Published in:
J. Artif. Intell. Res., Vol. 63, 2018, pp. 1-49.
Summary
Coordinating agents to complete a set of tasks with intercoupled temporal and resource constraints is computationally challenging, yet human domain experts can solve these difficult scheduling problems using paradigms learned through years of apprenticeship. A process for manually codifying this domain knowledge within a computational framework is necessary to scale beyond the "single-expert, single-trainee" apprenticeship model. However, human domain experts often have difficulty describing their decision-making processes. We propose a new approach for capturing this decision-making process through counterfactual reasoning in pairwise comparisons. Our approach is model-free and does not require iterating through the state space. We demonstrate that this approach accurately learns multifaceted heuristics on a synthetic and real world data sets. We also demonstrate that policies learned from human scheduling demonstration via apprenticeship learning can substantially improve the efficiency of schedule optimization. We employ this human-machine collaborative optimization technique on a variant of the weapon-to-target assignment problem. We demonstrate that this technique generates optimal solutions up to 9.5 times faster than a state-of-the-art optimization algorithm.
Summary
Coordinating agents to complete a set of tasks with intercoupled temporal and resource constraints is computationally challenging, yet human domain experts can solve these difficult scheduling problems using paradigms learned through years of apprenticeship. A process for manually codifying this domain knowledge within a computational framework is necessary to scale...
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Modeling and validation of a mm-wave shaped dielectric lens antenna
July 29, 2018
Conference Paper
Published in:
2018 Int. Applied Computational Electromagnetics Society Symp., ACES, 29 July - 1 August 2018.
Summary
The modeling and validation of a 33 GHz shaped dielectric antenna design is investigated. The electromagnetic modeling was performed in both WIPL-D and FEKO, and was used to validate the antenna design prior to fabrication of the lens. It is shown that both WIPL-D and FEKO yield similarly accurate results as compared to measured far-field gain radiation patterns.
Peregrine: 3-D network localization and navigation
November 8, 2017
Conference Paper
Published in:
IEEE 9th Latin-American Conf. on Communications, LATINCOM, 8-10 November 2017.
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Summary
Location-aware devices will create new services and applications in emerging fields such as autonomous driving, smart cities, and the Internet of Things. Many existing localization systems rely on anchors such as satellites at known positions which broadcast radio signals. However, such signals may be blocked by obstacles, corrupted by multipath propagation, or provide insufficient localization accuracy. Therefore, ubiquitous localization remains an extremely challenging problem. This paper introduces Peregrine, a 3-D cooperative network localization and navigation (NLN) system. Peregrine nodes are low-cost business-card-sized devices, consisting of a microprocessor, a commercially available ultra-wideband (UWB) radio module, and a small battery. Recently developed distributed algorithms are used in Peregrine to solve the highly interrelated problems of node inference and node activation in real-time, enabling resource efficiency, scalability, and accuracy for NLN. Node inference – based on the recently introduced sigma point belief propagation (SPBP) algorithm – enables spatiotemporal cooperation in realtime and estimates the nodes' positions accurately from UWB distance measurements. A distributed node activation algorithm controls channel access to improve the efficiency and reduce the localization error of the network. Contributions of each algorithmic component to overall system performance are validated through indoor localization experiments. Our results show that Peregrine achieves decimeter-level 3-D position accuracy in a challenging propagation environment.
Summary
Location-aware devices will create new services and applications in emerging fields such as autonomous driving, smart cities, and the Internet of Things. Many existing localization systems rely on anchors such as satellites at known positions which broadcast radio signals. However, such signals may be blocked by obstacles, corrupted by multipath...
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