Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2006. / Includes bibliographical references (p. 121-126). / This thesis proposes, develops and validates a methodology to quantify the complexity of air traffic control (ATC) human-machine interaction (HMI). Within this context, complexity is defined as the minimum amount of information required to describe the human machine interaction process in some fixed description language and chosen level of detail. The methodology elicits human information processing via cognitive task analysis (CTA) and expresses the HMI process algorithmically as a cognitive interaction algorithm (CIA). The CIA is comprised of multiple functions which formally describe each of the interaction processes required to complete a nominal set of tasks using a certain machine interface. Complexities of competing interface and task configurations are estimated by weighted summations of the compressed information content of the associated CIA functions. This information compression removes descriptive redundancy and approximates the minimum description length (MDL) of the CIA. The methodology is applied to a representative en-route ATC task and interface, and the complexity measures are compared to performance results obtained experimentally by human-in-the-loop simulations. / (cont.) It is found that the proposed complexity analysis methodology and resulting complexity metrics are able to predict trends in operator performance and workload. This methodology would allow designers and evaluators of human supervisory control (HSC) interfaces the ability to conduct complexity analyses and use complexity measures to more objectively select between competing interface and task configurations. Such a method could complement subjective interface evaluations, and reduce the amount of costly experimental testing. / by Christos George Tsonis. / S.M.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1998. / Includes bibliographical references (p. 219-221). / by Arnaud Irving Wisnia. / M.S.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005. / Includes bibliographical references (p. 99-102). / As the field of robotics continues to mature, individual robots are increasingly capable of performing multiple complex tasks. As a result, the ability for robots to move autonomously through their environments is a fundamental necessity. If perfect knowledge of the robot's position is available, the robot motion planning problem can be solved efficiently using any of a number of existing algorithms. Frequently though, the robot's position can only be estimated using incomplete and imperfect information from its sensors and an approximate model of its dynamics. Algorithms which assume perfect knowledge of the robot's position can still be applied by treating the mean or maximum likelihood estimate of the robot's position as certain. However, unless the uncertainty in the agent's position is very small, this approach is not reliable. In order to perform optimally in this situation, planners, such as the partially observable Markov decision process, plan over the entire set of beliefs (distributions over the robot's position). Unfortunately, this approach is only tractable for problems with very few states. Between these two extreme approaches, however, lies a continuum of possible planners which plan over a subset of the belief space. The difficulty that these planners face is choosing and representing a minimal subset of the belief space which spans the set of beliefs that the robot will actually experience. In this paper, we show that there exists a very natural such set, the set, of Gaussian beliefs. By combining an extended Kalman filter with an augmented Markov decision process, we create a path planner which efficiently plans over a discrete approximation of the set of Gaussian beliefs. / (cont.) The resulting planner is demonstrated via simulation to be both computationally tractable and robust to uncertainty in the robot's position. / by Peter Hans Lommel. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 105-113). / Blast-induced TBI has gained prominence in recent years due to the conflicts in Iraq and Afghanistan, yet little is known about the mechanical effects of blasts on the human head; no injury thresholds have been established for blast effects on the head, and even direct transmission of the shock wave to the intracranial cavity is disputed. Still less is known about how personal protective equipment such as the Advanced Combat Helmet (ACH) affect the brain's response to blasts. The goal of this thesis is to investigate the mechanical response of the human brain to blasts and to study the effect of the ACH on the blast response of the head. To that end, a biofidelic computational model of the human head consisting of 11 distinct structures was developed from high-resolution medical imaging data. The model, known as the DVBIC/MIT Full Head Model (FHM), was subjected to blasts with incident overpressures of 6 atm and 30 atm and to a 5 m/s lateral impact. Results from the simulations demonstrate that blasts can penetrate the intracranial cavity and generate intracranial pressures that exceed the pressures produced during impact; the results suggest that blasts can plausibly directly cause traumatic brain injury. Subsequent investigation of the effect of the ACH on the blast response of the head found that the ACH provided minimal mitigation of blast effects. Results from the simulations conducted with the FHM extended to include the ACH suggest that the ACH can slightly reduce peak pressure magnitudes and delay peak pressure arrival times, but the benefits are minimal because the ACH does not protect the main pathways of load transmission from the blast to brain tissue. A more effective blast mitigation strategy might involve altering the helmet design to more completely surround the head in order to protect it from direct exposure to blast waves. / by Michelle K. Nyein. / S.M.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2003. / Includes bibliographical references (p. 89). / by Jean-Benoît Ferry. / S.M.

Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged student-submitted from PDF version of thesis. / Includes bibliographical references (pages 98-101). / This research conducts a broad systems-based analysis of CubeSat engineering, with a focus on testing, failures, and their relationship to program cost, in order to assess multiple build approaches with a goal of maintaining the advantages of CubeSat missions while increasing reliability. In this work, the multiple approaches are called "beta build strategies," and we show that satellite engineering groups with minimal experience can increase their probability of success by building two flight-model versions of their satellite, allowing for more exhaustive and potentially failure-inducing testing to be conducted on the first (beta version) satellite. This differentiates itself from the standard CubeSat build approach, which is typically to build a flat sat, then an engineering model, and then a flight model of the satellite. Frequently with CubeSat development, the additional expense of building a flight-like engineering model is avoided. However, in this work we consider the probability of success and overall cost impact for multiple approaches toward the flight build. We find that by spending an additional 33% of the planned program cost, a team which plans to take this alternate approach from the beginning can build and launch two flight-model versions of their spacecraft, increasing probability of success by 30%. This cost corresponds to a 40% saving from the scenario in which the decision to build a second flight-model spacecraft is made only after the first fails. The question which this analysis tries to answer is not, "how does a group spend the least amount of money to get their first CubeSat into space?" but rather, "how does a group spend the least amount of money to get a CubeSat into space that works?" / by Zachary Scott Decker. / S.M.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 129-148). / In the recent years there has been a growing interest in studying electromagnetic wave propagation at the nanoscale. The interaction of light with metallic nanostructures produces a collective excitation of conduction electrons at the metal surface, also known as surface plasmons. These plasmonic resonances enable an unprecedented control of light by confining the electromagnetic field to regions well beyond the diffraction limit, thereby leading to nearfield enhancements of the incident wave of several orders of magnitude. These remarkable properties have motivated the application of plasmonic devices in sensing, nano-resolution imaging, energy harvesting, nanoscale electronics and cancer treatment. Despite state-of-the-art nanofabrication techniques are used to realize plasmonic devices, their performance is severely impacted by fabrication uncertainties arising from extreme manufacturing constraints. Mathematical modeling and numerical simulation are therefore essential to accurately predict the response of the physical system, and must be incorporated in the design process. Nonetheless, plasmonic simulations present notable challenges. From the physical perspective, the realistic behavior of conduction electrons in metallic nanostructures is not captured by Maxwell's equations, thus requiring additional modeling. From the simulation perspective, the disparity in length scales stemming from the extreme field localization exceeds the capabilities of most numerical simulation schemes. In addition, relevant data such as optical constants or geometry specifications are typically subject to measurement and manufacturing errors, hence simulations need to accommodate uncertainty in the data. In this thesis we present a collection of numerical methods to efficiently simulate electromagnetic wave propagation through metallic nanostructures. Firstly, we develop the hybridizable discontinuous Galerkin (HDG) method for Maxwell's equations augmented with the hydrodynamic model for metals, which accounts for the nonlocal interactions between electrons that become predominant at nanometric regimes. Secondly, we develop a reduced order modeling (ROM) framework for Maxwell's equations with the HDG method, enabling the incorporation of material and geometric uncertainties in the simulations. The result is a family of surrogate models that produces accurate yet inexpensive simulations of plasmonic devices. Finally, we apply these approaches to the study of periodic annular nanogaps, and present parametric analyses, verification with experimental data and design of novel structures. / by Ferran Vidal-Codina. / Ph. D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1988. / Includes bibliographical references. / by Michael R. Fisher, Jr. / Ph.D.

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2007. / Includes bibliographical references (p. 307-324). / The capability to routinely perform autonomous docking is a key enabling technology for future space exploration, as well as assembly and servicing missions for spacecraft and commercial satellites. Particularly, in more challenging situations where the target spacecraft or satellite is tumbling, algorithms and strategies must be implemented to ensure the safety of both docking entities in the event of anomalies. However, difficulties encountered in past docking missions conducted with expensive satellites on orbit have indicated a lack of maturity in the technologies required for such operations. Therefore, more experimentation must be performed to improve the current autonomous docking capabilities. The main objectives of the research presented in this thesis are to develop a guidance, navigation and control (GN&C) architecture that enables the safe and fuel-efficient docking with a free tumbling target in the presence of obstacles and anomalies, and to develop the software tools and verification processes necessary in order to successfully demonstrate the GN&C architecture in a relevant environment. The GN&C architecture was developed by integrating a spectrum of GN&C algorithms including estimation, control, path planning, and failure detection, isolation and recovery algorithms. / (cont.) The algorithms were implemented in GN&C software modules for real-time experimentation using the Synchronized Position Hold Engage and Reorient Experimental Satellite (SPHERES) facility that was created by the MIT Space Systems Laboratory. Operated inside the International Space Station (ISS), SPHERES allow the incremental maturation of formation flight and autonomous docking algorithms in a risk-tolerant, microgravity environment. Multiple autonomous docking operations have been performed in the ISS to validate the GN&C architecture. These experiments led to the first autonomous docking with a tumbling target ever achieved in microgravity. Furthermore, the author also demonstrated successful docking in spite of the presence of measurement errors that were detected and rejected by an online fault detection algorithm. The results of these experiments will be discussed in this thesis. Finally, based on experiments in a laboratory environment, the author establishes two processes for the verification of GN&C software prior to on-orbit testing on the SPHERES testbed. / by Simon Nolet. / Sc.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 235-239). / I envision a future where collaboration between humans and robots will be indispensable to our work in numerous domains, ranging from surgery to space exploration. The success of these systems will depend in part on the ability of robots to integrate within existing human teams. The goal of this thesis is to develop robot partners that we can work with easily and naturally, inspired by the way we work with other people. My hypothesis is that human-robot team performance improves when a robot teammate emulates the effective coordination behaviors observed in human teams. I design and evaluate Chaski, a robot plan execution system that uses insights from human-human teaming to make human-robot teaming more natural and fluid. Chaski is a task-level executive that enables a robot to robustly anticipate and adapt to other team members. Chaski also emulates a human's response to implicit communications, including verbal and gestural cues, and explicit commands. Development of such an executive is challenging because the robot must be able to make decisions very quickly in response to a human's actions. In the past, the ability of robots to demonstrate these capabilities has been limited by the time-consuming computations required to anticipate a large set of possible futures. These computations result in execution delays that endanger the robot's ability to fulfill its role on the team. I significantly improve the ability of a robot to adapt on-the-fly by generalizing the state-of-the-art in dynamic plan execution to support just-in-time task assignment and scheduling. My methods provide a novel way to represent the robot's plan compactly. This compact representation enables the plan to be incrementally updated very quickly. I empirically demonstrate that, compared to prior work in this area, my methods increase the speed of online computation by one order of magnitude on average. I also show that 89% of moderately-sized benchmark plans are updated within human reaction time using Chaski, compared to 24% for prior art. I evaluate Chaski in human subject experiments in which a person works with a mobile and dexterous robot to collaboratively assemble structures using building blocks. I measure team performances outcomes for robots controlled by Chaski compared to robots that are verbally commanded, step-by-step by the human teammate. I show that Chaski reduces the human's idle time by 85%, a statistically significant difference. This result supports the hypothesis that human-robot team performance is improved when a robot emulates the effective coordination behaviors observed in human teams. / by Julie A. Shah. / Ph.D.