This research focuses mainly on employing tunable materials to achieve dynamic radiative properties for spacecraft and building thermal management. A secondary objective is to investigate tunable materials for optical propulsion applications. The primary material investigated is vanadium dioxide (VO2), which is a thermochromic material with an insulator-to-metal phase transition. VO2 typically undergoes a dramatic shift in optical properties at T = 341 K, which can be reduced through a variety of techniques to a temperature more suitable for thermal control applications. A VO2-based Fabry-Perot variable emitter is designed, fabricated, characterized, and experimentally demonstrated. The designed emitter has high emissivity when the radiating surface temperature is above 345 K and low emissivity when the temperature is less than 341 K. A uniaxial transfer matrix method and Bruggeman effective medium theory are both introduced to model the anisotropic properties of the VO2 to facilitate the design of multilayer VO2-based devices. A new furnace oxidation process is developed for fabricating high quality VO2 and the resulting thin films undergo comprehensive material and optical characterizations. The corresponding measurement platform is developed to measure the temperature-dependent transmittance and reflectance of the fabricated Fabry-Perot samples. The variable heat rejection of the fabricated samples is demonstrated via bell jar and cryothermal vacuum calorimetry measurements. Thermal modeling of a spacecraft equipped with variable emittance radiators is also conducted to elucidate the requirements and the impact for thermochromic variable emittance technology.
The potential of VO2 to be used as an optical force modulating device is also investigated for spacecraft micropropulsion. The preliminary design considers a Fabry-Perot cavity with an anti-reflection coating which switches between an absorptive “off” state (for insulating VO2) and a reflective “on” state (for metallic VO2), thereby modulating the incident solar radiation pressure. The visible and near-infrared optical properties of the fabricated vanadium dioxide are examined to determine if there is a sufficient optical property shift in those regimes for a tunable device.

In order to deploy autonomous multi-robot teams for humanitarian demining in Colombia, two key problems need to be addressed. First, a robotic controller with limited power that can completely cover a dynamic search area is needed. Second, the Colombian National Army (COLAR) needs to increase its science, technology and innovation (STI) capacity to help develop, build and maintain such robots. Using Thangavelautham's (2012, 2017) Artificial Neural Tissue (ANT) control algorithm, a robotic controller for an autonomous multi-robot team was developed. Trained by a simple genetic algorithm, ANT is an artificial neural network (ANN) controller with a sparse, coarse coding network architecture and adaptive activation functions. Starting from the exterior of open, basic geometric grid areas, computer simulations of an ANT multi-robot team with limited time steps, no central controller and limited a priori information, covered some areas completely in linear time, and other areas near completely in quasi-linear time, comparable to the theoretical cover time bounds of grid-based, ant pheromone, area coverage algorithms. To mitigate catastrophic forgetting, a new learning method for ANT, Lifelong Adaptive Neuronal Learning (LANL) was developed, where neural network weight parameters for a specific coverage task were frozen, and only the activation function and output behavior parameters were re-trained for a new coverage task. The performance of the LANL controllers were comparable to training all parameters ab initio, for a new ANT controller for the new coverage task.

To increase COLAR's STI capacity, a proposal for a new STI officer corps, Project ÉLITE (Equipo de Líderes en Investigación y Tecnología del Ejército) was developed, where officers enroll in a research intensive, master of science program in applied mathematics or physics in Colombia, and conduct research in the US during their final year. ÉLITE is inspired by the Israel Defense Forces Talpiot program.

Achieving human level intelligence is a long-term goal for many Artificial Intelligence (AI) researchers. Recent developments in combining deep learning and reinforcement learning helped us to move a step forward in achieving this goal. Reinforcement learning using a delayed reward mechanism is an approach to machine intelligence which studies decision making with control and how a decision making agent can learn to act optimally in an environment-unaware conditions.

Q-learning is one of the model-free reinforcement directed learning strategies which uses temporal differences to estimate the performances of state-action pairs called Q values. A simple implementation of Q-learning algorithm can be done using a Q table memory to store and update the Q values. However, with an increase in state space data due to a complex environment, and with an increase in possible number of actions an agent can perform, Q table reaches its space limit and would be difficult to scale well. Q-learning with neural networks eliminates the use of Q table by approximating the Q function using neural networks.

Autonomous agents need to develop cognitive properties and become self-adaptive to be deployable in any environment. Reinforcement learning with Q-learning have been very efficient in solving such problems. However, embedded systems like space rovers and autonomous robots rarely implement such techniques due to the constraints faced like processing power, chip area, convergence rate and cost of the chip. These problems present a need for a portable, low power, area efficient hardware accelerator to accelerate the process of such learning.

This problem is targeted by implementing a hardware schematic architecture for Q-learning using Artificial Neural networks. This architecture exploits the massive parallelism provided by neural network with a dedicated fine grain parallelism provided by a Field Programmable Gate Array (FPGA) thereby processing the Q values at a high throughput. Mars exploration rovers currently use Xilinx-Space-grade FPGA devices for image processing, pyrotechnic operation control and obstacle avoidance. The hardware resource consumption for the architecture has been synthesized considering Xilinx Virtex7 FPGA as the target device.

Space systems such as communication satellites, earth observation satellites and telescope require accurate pointing to observe fixed targets over prolonged time. These systems typically use reaction wheels to slew the spacecraft and gimballing systems containing motors to achieve precise pointing. Motor based actuators have limited life as they contain moving parts that require lubrication in space. Alternate methods have utilized piezoelectric actuators. This paper presents Shape memory alloys (SMA) actuators for control of a deployable antenna placed on a satellite. The SMAs are operated as a series of distributed linear actuators. These distributed linear actuators are not prone to single point failures and although each individual actuator is imprecise due to hysteresis and temperature variation, the system as a whole achieves reliable results. The SMAs can be programmed to perform a series of periodic motion and operate as a mechanical guidance system that is not prone to damage from radiation or space weather. Efforts are focused on developing a system that can achieve 1 degree pointing accuracy at first, with an ultimate goal of achieving a few arc seconds accuracy. Bench top model of the actuator system has been developed and working towards testing the system under vacuum. A demonstration flight of the technology is planned aboard a CubeSat.

Surface exploration of the Moon and Asteroids can provide important information to scientists regarding the origins of the solar-system and life . Small robots and sensor modules can enable low-cost surface exploration. In the near future, they are the main machines providing these answers. Advanced in electronics, sensors and actuators enable ever smaller platforms, with compromising functionality. However similar advances haven’t taken place for power supplies and thermal control system. The lunar south pole has temperatures in the range of -100 to -150 oC. Similarly, asteroid surfaces can encounter temperatures of -150 oC. Most electronics and batteries do not work below -40 oC. An effective thermal control system is critical towards making small robots and sensors module for extreme environments feasible.

In this work, the feasibility of using thermochemical storage materials as a possible thermal control solution is analyzed for small robots and sensor modules for lunar and asteroid surface environments. The presented technology will focus on using resources that is readily generated as waste product aboard a spacecraft or is available off-world through In-Situ Resource Utilization (ISRU).

In this work, a sensor module for extreme environment has been designed and prototyped. Our intention is to have a network of tens or hundreds of sensor modules that can communicate and interact with each other while also gathering science data. The design contains environmental sensors like temperature sensors and IMU (containing accelerometer, gyro and magnetometer) to gather data. The sensor module would nominally contain an electrical heater and insulation. The thermal heating effect provided by this active heater is compared with the proposed technology that utilizes thermochemical storage chemicals.

Our results show that a thermochemical storage-based thermal control system is feasible for use in extreme temperatures. A performance increase of 80% is predicted for the sensor modules on the asteroid Eros using thermochemical based storage system. At laboratory level, a performance increase of 8 to 9 % is observed at ambient temperatures of -32oC and -40 oC.

In-situ exploration of planetary bodies such as Mars or the Moon have provided geologists and planetary scientists a detailed understanding of how these bodies formed and evolved. In-situ exploration has aided in the quest for water and life-supporting chemicals. In-situ exploration of Mars carried out by large SUV-sized rovers that travel long distance, carry sophisticated onboard laboratories to perform soil analysis and sample collection. But their large size and mobility method prevents them from accessing or exploring extreme environments, particularly caves, canyons, cliffs and craters.

This work presents sub- 2 kg ball robots that can roll and hop in low gravity environments. These robots are low-cost enabling for one or more to be deployed in the field. These small robots can be deployed from a larger rover or lander and complement their capabilities by performing scouting and identifying potential targets of interest. Their small size and ball shape allow them to tumble freely, preventing them from getting stuck. Hopping enables the robot to overcome obstacles larger than the size of the robot.

The proposed ball-robot design consists of a spherical core with two hemispherical shells with grouser which act as wheels for small movements. These robots have two cameras for stereovision which can be used for localization. Inertial Measurement Unit (IMU) and wheel encoder are used for dead reckoning. Communication is performed using Zigbee radio. This enables communication between a robot and a lander/rover or for inter-robot communication. The robots have been designed to have a payload with a 300 gram capacity. These may include chemical analysis sensors, spectrometers and other small sensors.

The performance of the robot has been evaluated in a laboratory environment using Low-gravity Offset and Motion Assistance Simulation System (LOMASS). An evaluation was done to understand the effect of grouser height and grouser separation angle on the performance of the robot in different terrains. The experiments show with higher grouser height and optimal separation angle the power requirement increases but an increase in average robot speed and traction is also observed. The robot was observed to perform hops of approximately 20 cm in simulated lunar condition. Based on theoretical calculations, the robot would be able to perform 208 hops with single charge and will operate for 35 minutes. The study will be extended to operate multiple robots in a network to perform exploration. Their small size and cost makes it possible to deploy dozens in a region of interest. Multiple ball robots can cooperatively perform unique in-situ science measurements and analyze a larger surface area than a single robot alone on a planet surface.

CubeSats offer a compelling pathway towards lowering the cost of interplanetary exploration missions thanks to their low mass and volume. This has been possible due to miniaturization of electronics and sensors and increased efficiency of photovoltaics. Interplanetary communication using radio signals requires large parabolic antennas on the spacecraft and this often exceeds the total volume of CubeSat spacecraft. Mechanical deployable antennas have been proposed that would unfurl to form a large parabolic dish. These antennas much like an umbrella has many mechanical moving parts, are complex and are prone to jamming. An alternative are inflatables, due to their tenfold savings in mass, large surface area and very high packing efficiency of 20:1. The present work describes the process of designing and building inflatable parabolic reflectors for small satellite radio communications in the X band.

Tests show these inflatable reflectors to provide significantly higher gain characteristics as compared to conventional antennas. This would lead to much higher data rates from low earth orbits and would provide enabling communication capabilities for small satellites in deeper space. This technology is critical to lowering costs of small satellites while enhancing their capabilities.

Principle design challenges with inflatable membranes are maintaining accurate desired shape, reliable deployment mechanism and outer space environment protection. The present work tackles each of the mentioned challenges and provides an



understanding towards future work. In the course of our experimentation we have been able to address these challenges using building techniques that evolved out of a matured understanding of the inflation process.

Our design is based on low cost chemical sublimates as inflation substances that use a simple mechanism for inflation. To improve the reliability of the inflated shape, we use UV radiation hardened polymer support structures. The novelty of the design lies in its simplicity, low cost and high reliability. The design and development work provides an understanding towards extending these concepts to much larger deployable structures such as solar sails, inflatable truss structures for orbit servicing and large surface area inflatables for deceleration from hypersonic speeds when re-entering the atmosphere.

There has been a vast increase in applications of Unmanned Aerial Vehicles (UAVs) in civilian domains. To operate in the civilian airspace, a UAV must be able to sense and avoid both static and moving obstacles for flight safety. While indoor and low-altitude environments are mainly occupied by static obstacles, risks in space of higher altitude primarily come from moving obstacles such as other aircraft or flying vehicles in the airspace. Therefore, the ability to avoid moving obstacles becomes a necessity

for Unmanned Aerial Vehicles.

Towards enabling a UAV to autonomously sense and avoid moving obstacles, this thesis makes the following contributions. Initially, an image-based reactive motion planner is developed for a quadrotor to avoid a fast approaching obstacle. Furthermore, A Dubin’s curve based geometry method is developed as a global path planner for a fixed-wing UAV to avoid collisions with aircraft. The image-based method is unable to produce an optimal path and the geometry method uses a simplified UAV model. To compensate

these two disadvantages, a series of algorithms built upon the Closed-Loop Rapid Exploratory Random Tree are developed as global path planners to generate collision avoidance paths in real time. The algorithms are validated in Software-In-the-Loop (SITL) and Hardware-In-the-Loop (HIL) simulations using a fixed-wing UAV model and in real flight experiments using quadrotors. It is observed that the algorithm enables a UAV to avoid moving obstacles approaching to it with different directions and speeds.

CubeSats are a newly emerging, low-cost, rapid development platform for space exploration research. They are small spacecraft with a mass and volume of up to 12 kg and 12,000 cm3, respectively. To date, CubeSats have only been flown in Low Earth Orbit (LEO), though a large number are currently being designed to be dropped off by a mother ship on Earth escape trajectories intended for Lunar and Martian flyby missions. Advancements in propulsion technologies now enable these spacecraft to achieve capture orbits around the moon and Mars, providing a wealth of scientific data at low-cost. However, the mass, volume and launch constraints of CubeSats severely limit viable propulsion options.

We present an innovative propulsion solution using energy generated by onboard photovoltaic panels to electrolyze water, thus producing combustible hydrogen and oxygen for low-thrust applications. Water has a high storage density allowing for sufficient fuel within volume constraints. Its high enthalpy of formation provides more fuel that translates into increased ∆V and vastly reduced risk for the launch vehicle. This innovative technology poses significant challenges including the design and operation of electrolyzers at ultra-cold temperatures, the efficient separation of the resultant hydrogen and oxygen gases from liquid water in a microgravity environment, as well as the effective utilization of thrust to produce desired trajectories.

Analysis of the gas combustion and flow through the nozzle using both theoretical equations and finite-volume CFD modeling suggests an expected specific impulse of 360 s. Preliminary results from AGI's Satellite Toolkit (STK) indicate that the ΔV produced by the system for an 8kg CubeSat with 6kg of propellant in a LEO orbit (370 km altitude) is sufficient for an earth escape trajectory, lunar capture orbit or even a Mars capture orbit. These results suggest a promising pathway for an in-depth study supported by laboratory experiments to characterize the strengths and weaknesses of the proposed concept.

This project is to develop a new method to generate GPS waypoints for better terrain mapping efficiency using an UAV. To create a map of a desired terrain, an UAV is used to capture images at particular GPS locations. These images are then stitched together to form a complete map of the terrain. To generate a good map using image stitching, the images are desired to have a certain percentage of overlap between them. In high windy condition, an UAV may not capture image at desired GPS location, which in turn interferes with the desired percentage of overlap between images; both frontal and sideways; thus causing discrepancies while stitching the images together. The information about the exact GPS locations at which the images are captured can be found on the flight logs that are stored in the Ground Control Station and the Auto pilot board. The objective is to look at the flight logs, predict the waypoints at which the UAV might have swayed from the desired flight path. If there are locations where flight swayed from intended path, the code should generate a new set of waypoints for a correction flight. This will save the time required for stitching the images together, thus making the whole process faster and more efficient.