Hi! I’m currently the Deputy Director of the Hawaii Space Flight Laboratory (HSFL) and Assistant Specialist Faculty with the Hawaii Institute of Geophysics and Planetology (HIGP) at the University of Hawaii at Manoa. This page has some information about my work. If you have questions don’t hesitate to contact me.
Things that I most like to do:
- Small Satellites and anything related
- Dynamics, Guidance, Navigation and Control (GNC) of Autonomous Robots
- Space Mission Operations Software (COSMOS)
- Flight Software, C++11 is amazing …
Click to see my Research Gate profile.
Click to see my Google Scholar profile.
Title: Multi-agent robotic systems and applications for satellite missions
“Each of us is here for a brief sojourn; for what purpose he knows not, though he senses it. But without deeper reflection one knows from daily life that one exists for other people” Albert Einstein (1879 – 1955)
A revolution in the space sector is happening. It is expected that in the next decade there will be more satellites launched than in the previous sixty years of space exploration. Major challenges are associated with this growth of space assets such as the autonomy and management of large groups of satellites, in particular with small satellites. There are two main objectives for this work. First, a flexible and distributed software architecture is presented to expand the possibilities of spacecraft autonomy and in particular autonomous motion in attitude and position. The approach taken is based on the concept of distributed software agents, also referred to as multi-agent robotic system. Agents are defined as software programs that are social, reactive and proactive to autonomously maximize the chances of achieving the set goals. Part of the work is to demonstrate that a multi-agent robotic system is a feasible approach for different problems of autonomy such as satellite attitude determination and control and autonomous rendezvous and docking. The second main objective is to develop a method to optimize multi-satellite configurations in space, also known as satellite constellations. This automated method generates new optimal mega-constellations designs for Earth observations and fast revisit times on large ground areas. The optimal satellite constellation can be used by researchers as the baseline for new missions. The first contribution of this work is the development of a new multi-agent robotic system for distributing the attitude determination and control subsystem for HiakaSat. The multi-agent robotic system is implemented and tested on the satellite hardware-in-the-loop testbed that simulates a representative space environment. The results show that the newly proposed system for this particular case achieves an equivalent control performance when compared to the monolithic implementation. In terms on computational efficiency it is found that the multi-agent robotic system has a consistent lower CPU load of 0.29 ± 0.03 compared vi to 0.35 ± 0.04 for the monolithic implementation, a 17.1 % reduction. The second contribution of this work is the development of a multi-agent robotic system for the autonomous rendezvous and docking of multiple spacecraft. To compute the maneuvers guidance, navigation and control algorithms are implemented as part of the multi-agent robotic system. The navigation and control functions are implemented using existing algorithms, but one important contribution of this section is the introduction of a new six degrees of freedom guidance method which is part of the guidance, navigation and control architecture. This new method is an explicit solution to the guidance problem, and is particularly useful for real time guidance for attitude and position, as opposed to typical guidance methods which are based on numerical solutions, and therefore are computationally intensive. A simulation scenario is run for docking four CubeSats deployed radially from a launch vehicle. Considering fully actuated CubeSats, the simulations show docking maneuvers that are successfully completed within 25 minutes which is approximately 30% of a full orbital period in low earth orbit. The final section investigates the problem of optimization of satellite constellations for fast revisit time, and introduces a new method to generate different constellation configurations that are evaluated with a genetic algorithm. Two case studies are presented. The first is the optimization of a constellation for rapid coverage of the oceans of the globe in 24 hours or less. Results show that for an 80 km sensor swath width 50 satellites are required to cover the oceans with a 24 hour revisit time. The second constellation configuration study focuses on the optimization for the rapid coverage of the North Atlantic Tracks for air traffic monitoring in 3 hours or less. The results show that for a fixed swath width of 160 km and for a 3 hour revisit time 52 satellites are required
Title: A BIOLOGICALLY INSPIRED METHODOLOGY FOR MULTI-DISCIPLINARY DESIGN OPTIMIZATION
”If there occur some changes in nature, the amount of action necessary for this change must be as small as possible.”
Pierre Louis Moreau de Maupertuis, 1698 – 1759;
French mathematician who formulated the principle of least action.
Optimization problems in engineering are of major importance for the development of new structures, new materials, and even for new ways of improving engineering that are so demanding in today’s industry. The development of a biologically inspired methodology brings new ways for topology optimization to be applied in a multidisciplinary design approach. The process developed in this thesis extends the methodology proposed by Kobayashi for engineering designs to multiply connected regions. The methodology is based on a cellular division model for developing the design topology. The topology generated is then improved using a Genetic Algorithm. The methodology is demonstrated in the design of a structural panel from a satellite at launching conditions. Software was developed to illustrate the applicability of the proposed design approach. The results show how the method improves a given structural problem and compares it to a traditional engineering design.
Keywords: Multidisciplinary Design Optimization, Map L-system, Biologically Inspired Structures, Satellites.
>> Thesis Document
>> Thesis Presentation
Miguel A. Nunes
University of Hawaii at Manoa
Hawaii Space Flight Laboratory
1680 East-West Road, POST 501
Honolulu, HI 96822, U.S.A.
Miguel (dot) Nunes (at) hawaii (dot) edu
+1 808-956-0441 (line)