MIT Space Engineering Research Center

The Space Engineering Research Center (SERC) at MIT, started in Jul. 1988, has completed two years of research. The Center is approaching the operational phase of its first testbed, is midway through the construction of a second testbed, and is in the design phase of a third. We presently have seven participating faculty, four participating staff members, ten graduate students, and numerous undergraduates. This report reviews the testbed programs, individual graduate research, other SERC activities not funded by the Center, interaction with non-MIT organizations, and SERC milestones. Published papers made possible by SERC funding are included at the end of the report

Connected Attribute Filtering Based on Contour Smoothness

A new attribute measuring the contour smoothness of 2-D objects is presented in the context of morphological attribute filtering. The attribute is based on the ratio of the circularity and non-compactness, and has a maximum of 1 for a perfect circle. It decreases as the object boundary becomes irregular. Computation on hierarchical image representation structures relies on five auxiliary data members and is rapid. Contour smoothness is a suitable descriptor for detecting and discriminating man-made structures from other image features. An example is demonstrated on a very-high-resolution satellite image using connected pattern spectra and the switchboard platform

A Dynamical System-based Approach to Modeling Stable Robot Control Policies via Imitation Learning

Despite tremendous advances in robotics, we are still amazed by the proficiency with which humans perform movements. Even new waves of robotic systems still rely heavily on hardcoded motions with a limited ability to react autonomously and robustly to a dynamically changing environment. This thesis focuses on providing possible mechanisms to push the level of adaptivity, reactivity, and robustness of robotic systems closer to human movements. Specifically, it aims at developing these mechanisms for a subclass of robot motions called “reaching movements”, i.e. movements in space stopping at a given target (also referred to as episodic motions, discrete motions, or point-to-point motions). These reaching movements can then be used as building blocks to form more advanced robot tasks. To achieve a high level of proficiency as described above, this thesis particularly seeks to derive control policies that: 1) resemble human motions, 2) guarantee the accomplishment of the task (if the target is reachable), and 3) can instantly adapt to changes in dynamic environments. To avoid manually hardcoding robot motions, this thesis exploits the power of machine learning techniques and takes an Imitation Learning (IL) approach to build a generic model of robot movements from a few examples provided by an expert. To achieve the required level of robustness and reactivity, the perspective adopted in this thesis is that a reaching movement can be described with a nonlinear Dynamical System (DS). When building an estimate of DS from demonstrations, there are two key problems that need to be addressed: the problem of generating motions that resemble at best the demonstrations (the “how-to-imitate” problem), and most importantly, the problem of ensuring the accomplishment of the task, i.e. reaching the target (the “stability” problem). Although there are numerous well-established approaches in robotics that could answer each of these problems separately, tackling both problems simultaneously is challenging and has not been extensively studied yet. This thesis first tackles the problem mentioned above by introducing an iterative method to build an estimate of autonomous nonlinear DS that are formulated as a mixture of Gaussian functions. This method minimizes the number of Gaussian functions required for achieving both local asymptotic stability at the target and accuracy in following demonstrations. We then extend this formulation and provide sufficient conditions to ensure global asymptotic stability of autonomous DS at the target. In this approach, an estimation of the underlying DS is built by solving a constraint optimization problem, where the metric of accuracy and the stability conditions are formulated as the optimization objective and constraints, respectively. In addition to ensuring convergence of all motions to the target within the local or global stability regions, these approaches offer an inherent adaptability and robustness to changes in dynamic environments. This thesis further extends the previous approaches and ensures global asymptotic stability of DS-based motions at the target independently of the choice of the regression technique. Therefore, it offers the possibility to choose the most appropriate regression technique based on the requirements of the task at hand without compromising DS stability. This approach also provides the possibility of online learning and using a combination of two or more regression methods to model more advanced robot tasks, and can be applied to estimate motions that are represented with both autonomous and non-autonomous DS. Additionally, this thesis suggests a reformulation to modeling robot motions that allows encoding of a considerably wider set of tasks ranging from reaching movements to agile robot movements that require hitting a given target with a specific speed and direction. This approach is validated in the context of playing the challenging task of minigolf. Finally, the last part of this thesis proposes a DS-based approach to realtime obstacle avoidance. The presented approach provides a modulation that instantly modifies the robot’s motion to avoid collision with multiple static and moving convex obstacles. This approach can be applied on all the techniques described above without affecting their adaptability, swiftness, or robustness. The techniques that are developed in this thesis have been validated in simulation and on different robotic platforms including the humanoid robots HOAP-3 and iCub, and the robot arms KATANA, WAM, and LWR. Throughout this thesis we show that the DS-based approach to modeling robot discrete movements can offer a high level of adaptability, reactivity, and robustness almost effortlessly when interacting with dynamic environments

Application of CBIR techniques for the purpose of biometric identification based on human gait

Intenzivan razvoj informaciono-komunikacionih tehnologija otvorio je vrata primeni biometrijskih tehnologija u menadžmentu identiteta. Biometrijski modalitet koji ima veliki potencijal za primenu u praksi je ljudski hod. Njega odlikuju neinvazivnost i neintruzivnost. Ovakve osobine posebno pogoduju primeni u uslovima tehnologije prismotre. Zahvaljujući tome, ovaj biometrijski modalitet tokom prethodnih godina izaziva veliko interesovanje akademske zajednice. Ovo interesovanje rezultiralo je razvojem velikog broja pristupa za prepoznavanje osoba na osnovu hoda. Uprkos tome, primena biometrijskih tehnologija zasnovanih na ljudskom hodu u praksi i dalje zaostaje za dobro ustanovljenim modalitetima poput otiska prsta, lica ili glasa. Glavni razlog je nedostatak odgovarajućeg pristupa koji bi omogućio stabilnu primenu u realnim uslovima. Cilj ovog rada je predlog novog postupka za prepoznavanje osoba na osnovu hoda koji bi omogućio razvoj robusnog i pristupačnog biometrijskog sistema. Inicijalno, urađen je sveobuhvatan pregled oblasti i aktuelnih istraživanja na osnovu čega je predložen novi postupak. Predloženi postupak se zasniva na ideji da se sekvenca ljudskog hoda može predstaviti kao jedna nepomična 2D slika. Ovakav postupak omogućio bi da se za potrebe prepoznavanja primene generičke metode za pretragu slika na osnovu sadržaja. Na ovakav način problem bi bio prenet iz prostorno-vremenskog domena u prostorni domen, konkretno domen 2D nepomične slike, koji je poznat i u kome postoji veliki broj dokazanih rešenja. Za potrebe akvizicije, postupak se oslanja na novu tehnologiju iz oblasti interakcije čovek-računar, Microsoft Kinect. Na osnovu predloženog postupka razvijen je modularni laboratorijski prototip kao i okruženje za testiranje i evaluaciju. Naučna zasnovanost i opravdanost predloženog postupka proverena je nizom eksperimenata. Eksperimenti su organizovani na takav način da ispitaju različite faktore koji tokom primene postupka mogu uticati na konačne performanse u prepoznavanju. Na osnovu dobijenih rezultata može se zaključiti da predloženi postupak odlilkuje visok stepen robusnosti kao i visoka preciznost u prepoznavanju...Intense progress of information and communications technology enabled application of biometric technology in identity management. Human gait, as a biometric modality, has great potential for practical application. This is due to its noninvasive and nonintrusive nature. Surveillance technology is especially fertile ground for recognition based on human gait. These facts caused spike in academic interest for this biometric modality. This in turn resulted in development of large number of different approaches to human gait recognition. Nevertheless, practical application of biometric technology based on human gait still trails those well established modalities such as fingerprint, face or voice. Main reason for this is lacking of such approach that would enable stable use in realistic conditions. Goal of this paper is to propose a new approach for human gait recognition that would result in robust and affordable biometric system. Initially, a comprehensive review of research area and existing research was done that served as a base for the proposition of new approach. This new approach is based on the idea that human gait sequence can be represented as a single 2D still image. Using images would open the possibility of applying Content Based Image Retrieval (CBIR) techniques for the purpose of final recognition. This procedure shifts the problem form spatio-temporal towards spatial domain, specifically the space of 2D still image that is well researched and familiar. For acquisition purposes approach relies on new human-computer interaction technology, Microsoft Kinect. As proof of concept, a modular laboratory prototype was developed as well as environment for testing and evaluation. Foundation of the proposed approach was tested through a series of experiments. Empirical evaluation was performed in such a manner to investigate the influence of different contributing factors to system performance. Based on retrieved results a conclusion is reached that the proposed approach is highly robust and achieves high recognition rates..

Shielding Strategies for Human Space Exploration

A group of twenty-nine scientists and engineers convened a 'Workshop on Shielding Strategies for Human Space Exploration' at the Lyndon B. Johnson Space Center in Houston, Texas. The provision of shielding for a Mars mission or a Lunar base from the hazards of space radiations is a critical technology since astronaut radiation safety depends on it and shielding safety factors to control risk uncertainty appear to be great. The purpose of the workshop was to define requirements for the development and evaluation of high performance shield materials and designs and to develop ideas regarding approaches to radiation shielding. The workshop was organized to review the recent experience on shielding strategies gained in studies of the 'Space Exploration Initiative (SEI),' to review the current knowledge base for making shield assessment, to examine a basis for new shielding strategies, and to recommend a strategy for developing the required technologies for a return to the moon or for Mars exploration. The uniqueness of the current workshop arises from the expected long duration of the missions without the protective cover of the geomagnetic field in which the usually small and even neglected effects of the galactic cosmic rays (GCR) can no longer be ignored. It is the peculiarity of these radiations for which the inter-action physics and biological action are yet to be fully understood