Alan Aguilar

Alan Aguilar is first year Aerospace Engineering PhD student at Texas A&M University. His research focuses on decentralized planning for multi agent satellite systems, specifically for distributed Earth Observation Systems (EOS), with an interests in constellation design and optimization.

He is currently working on implementing a Consensus Constraint-Based Bundle Algorithm (CCBBA) as a decentralized planner for EOS. This is being done by implementing realistic astrodynamics and inter-satellite communication protocols to exploit the algorithm’s adaptive modularity capabilities and see its effects on mission performance for distributed and federated EOS constellations. This same project is also intended to measure overall mission capabilities and requirement satisfaction to create a holistic evaluation of a mission similar to the VASSAR methodology. This with the intention of creating a higher fidelity model that can then be then used in collaboration with VASSAR to perform trade-space exploration or design studies.

He is also a collaborator for the Distributed Spacecraft with Heuristic Intelligence to Enable Logistical Decisions (D-SHIELD) project under the supervision of Dr. Daniel Selva in collaboration with NASA Ames and BAERI, where he is in charge of satellite sizing and design for a novel distributed soil-moisture sensing EOS constellation.

During his undergrad he started his work on multi agent planning during his senior year, while a the same time working on a high-fidelity trajectory simulator for rockets for the University’s Sounding Rocketry Team. This simulator considered stochastic variables – such as wind direction, temperature, fuel amount uncertainty, among others – to provide a prediction for apogee and landing with statistical information and certainty.

Outside of research, he enjoys writing and performing music as well as having a passion for soccer and fencing.