A distributed algorithm for 2D shape duplication with smart pebble robots

We present our digital fabrication technique for manufacturing active objects in 2D from a collection of smart particles. Given a passive model of the object to be formed, we envision submerging this original in a vat of smart particles, executing the new shape duplication algorithm described in this paper, and then brushing aside any extra modules to reveal both the original object and an exact copy, side-by-side. Extensions to the duplication algorithm can be used to create a magnified version of the original or multiple copies of the model object. Our novel duplication algorithm uses a distributed approach to identify the geometric specification of the object being duplicated and then forms the duplicate from spare modules in the vicinity of the original. This paper details the duplication algorithm and the features that make it robust to (1) an imperfect packing of the modules around the original object; (2) missing communication links between neighboring modules; and (3) missing modules in the vicinity of the duplicate object(s). We show that the algorithm requires O(1) storage space per module and that the algorithm exchanges O(n) messages per module. Finally, we present experimental results from 60 hardware trials and 150 simulations. These experiments demonstrate the algorithm working correctly and reliably despite broken communication links and missing modules.United States. Army Research Office (Grant W911NF-08-1-0228)National Science Foundation (U.S.). Office of Emerging Frontiers in Research and Innovation (Grant 0735953)American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi

Shape formation by self-disassembly in programmable matter systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 225-236).Programmable matter systems are composed of small, intelligent modules able to form a variety of macroscale objects with specific material properties in response to external commands or stimuli. While many programmable matter systems have been proposed in fiction, (Barbapapa, Changelings from Star Trek, the Terminator, and Transformers), and academia, a lack of suitable hardware and accompanying algorithms prevents their full realization. With this thesis research, we aim to create a system of miniature modules that can form arbitrary structures on demand. We develop autonomous 12mm cubic modules capable of bonding to, and communicating with, four of their immediate neighbors. These modules are among the smallest autonomous modular robots capable of sensing, communication, computation, and actuation. The modules employ unique electropermanent magnet connectors. The four connectors in each module enable the modules to communicate and share power with their nearest neighbors. These solid-state connectors are strong enough for a single inter-module connection to support the weight of 80 other modules. The connectors only consume power when switching on or off; they have no static power consumption. We implement a number of low-level communication and control algorithms which manage information transfer between neighboring modules. These algorithms ensure that messages are delivered reliably despite challenging conditions. They monitor the state of all communication links and are able to reroute messages around broken communication links to ensure that they reach their intended destinations. In order to accomplish our long-standing goal of programmatic shape formation, we also develop a suite of provably-correct distributed algorithms that allow complex shape formation. The distributed duplication algorithm that we present allows the system to duplicate any passive object that is submerged in a collection of programmable matter modules. The algorithm runs on the processors inside the modules and requires no external intervention. It requires 0(1) storage and O(n) inter-module messages per module, where n is the number of modules in the system. The algorithm can both magnify and produce multiple copies of the submerged object. A programmable matter system is a large network of autonomous processors, so these algorithms have applicability in a variety of routing, sensor network, and distributed computing applications. While our hardware system provides a 50-module test-bed for the algorithms, we show, by using a unique simulator, that the algorithms are capable of operating in much larger environments. Finally, we perform hundreds of experiments using both the simulator and hardware to show how the algorithms and hardware operate in practice.by Kyle William Gilpin.Ph.D

Distributed algorithms for self-disassembly in modular robots

Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 225-226).We developed a modular robotic system that behaves as programmable matter. Specifically, we designed, implemented, and tested a collection of robots that, starting from an amorphous arrangement, can be assembled into arbitrary shapes and then commanded to self-disassemble in an organized manner. The 28 modules in the system were implemented as 1.77-inch autonomous cubes that were able to connect to and communicate with their immediate neighbors. Two cooperating microprocessors controlled the modules' magnetic connection mechanisms and infrared communication interfaces. We developed algorithms for the distributed communication and control of the system which allowed the modules to perform localization and distribute shape information in an efficient manner. When assembled into a structure, the modules formed a system which could be virtually sculpted using a computer interface which we also designed. By employing the sculpting process, we were able to accurately control the final shape assumed by the structure. Unnecessary modules disconnected from the structure and fell away. The results of close to 200 experiments showed the that the algorithms operated as expected and were able to successfully control the distributed system. We were able to quickly form one, two, and three dimensional structures.by Kyle W. Gilpin.M.Eng.and S.B

Skeeter Buster: A Stochastic, Spatially Explicit Modeling Tool for Studying Aedes aegypti Population Replacement and Population Suppression Strategies

Dengue is a viral disease that affects approximately 50 million people annually, and is estimated to result in 12,500 fatalities. Dengue viruses are vectored by mosquitoes, predominantly by the species Aedes aegypti. Because there is currently no vaccine or specific treatment, the only available strategy to reduce dengue transmission is to control the populations of these mosquitoes. This can be achieved by traditional approaches such as insecticides, or by recently developed genetic methods that propose the release of mosquitoes genetically engineered to be unable to transmit dengue viruses. The expected outcome of different control strategies can be compared by simulating the population dynamics and genetics of mosquitoes at a given location. Development of optimal control strategies can then be guided by the modeling approach. To that end, we introduce a new modeling tool called Skeeter Buster. This model describes the dynamics and the genetics of Ae. aegypti populations at a very fine scale, simulating the contents of individual houses, and even the individual water-holding containers in which mosquito larvae reside. Skeeter Buster can be used to compare the predicted outcomes of multiple control strategies, traditional or genetic, making it an important tool in the fight against dengue

Taking the pulse of Earth's tropical forests using networks of highly distributed plots

Tropical forests are the most diverse and productive ecosystems on Earth. While better understanding of these forests is critical for our collective future, until quite recently efforts to measure and monitor them have been largely disconnected. Networking is essential to discover the answers to questions that transcend borders and the horizons of funding agencies. Here we show how a global community is responding to the challenges of tropical ecosystem research with diverse teams measuring forests tree-by-tree in thousands of long-term plots. We review the major scientific discoveries of this work and show how this process is changing tropical forest science. Our core approach involves linking long-term grassroots initiatives with standardized protocols and data management to generate robust scaled-up results. By connecting tropical researchers and elevating their status, our Social Research Network model recognises the key role of the data originator in scientific discovery. Conceived in 1999 with RAINFOR (South America), our permanent plot networks have been adapted to Africa (AfriTRON) and Southeast Asia (T-FORCES) and widely emulated worldwide. Now these multiple initiatives are integrated via ForestPlots.net cyber-infrastructure, linking colleagues from 54 countries across 24 plot networks. Collectively these are transforming understanding of tropical forests and their biospheric role. Together we have discovered how, where and why forest carbon and biodiversity are responding to climate change, and how they feedback on it. This long-term pan-tropical collaboration has revealed a large long-term carbon sink and its trends, as well as making clear which drivers are most important, which forest processes are affected, where they are changing, what the lags are, and the likely future responses of tropical forests as the climate continues to change. By leveraging a remarkably old technology, plot networks are sparking a very modern revolution in tropical forest science. In the future, humanity can benefit greatly by nurturing the grassroots communities now collectively capable of generating unique, long-term understanding of Earth's most precious forests. Resumen Los bosques tropicales son los ecosistemas más diversos y productivos del mundo y entender su funcionamiento es crítico para nuestro futuro colectivo. Sin embargo, hasta hace muy poco, los esfuerzos para medirlos y monitorearlos han estado muy desconectados. El trabajo en redes es esencial para descubrir las respuestas a preguntas que trascienden las fronteras y los plazos de las agencias de financiamiento. Aquí mostramos cómo una comunidad global está respondiendo a los desafíos de la investigación en ecosistemas tropicales a través de diversos equipos realizando mediciones árbol por árbol en miles de parcelas permanentes de largo plazo. Revisamos los descubrimientos más importantes de este trabajo y discutimos cómo este proceso está cambiando la ciencia relacionada a los bosques tropicales. El enfoque central de nuestro esfuerzo implica la conexión de iniciativas locales de largo plazo con protocolos estandarizados y manejo de datos para producir resultados que se puedan trasladar a múltiples escalas. Conectando investigadores tropicales, elevando su posición y estatus, nuestro modelo de Red Social de Investigación reconoce el rol fundamental que tienen, para el descubrimiento científico, quienes generan o producen los datos. Concebida en 1999 con RAINFOR (Suramérica), nuestras redes de parcelas permanentes han sido adaptadas en África (AfriTRON) y el sureste asiático (T-FORCES) y ampliamente replicadas en el mundo. Actualmente todas estas iniciativas están integradas a través de la ciber-infraestructura de ForestPlots.net, conectando colegas de 54 países en 24 redes diferentes de parcelas. Colectivamente, estas redes están transformando nuestro conocimiento sobre los bosques tropicales y el rol de éstos en la biósfera. Juntos hemos descubierto cómo, dónde y porqué el carbono y la biodiversidad de los bosques tropicales está respondiendo al cambio climático y cómo se retroalimentan. Esta colaboración pan-tropical de largo plazo ha expuesto un gran sumidero de carbono y sus tendencias, mostrando claramente cuáles son los factores más importantes, qué procesos se ven afectados, dónde ocurren los cambios, los tiempos de reacción y las probables respuestas futuras mientras el clima continúa cambiando. Apalancando lo que realmente es una tecnología antigua, las redes de parcelas están generando una verdadera y moderna revolución en la ciencia tropical. En el futuro, la humanidad puede beneficiarse enormemente si se nutren y cultivan comunidades de investigadores de base, actualmente con la capacidad de generar información única y de largo plazo para entender los que probablemente son los bosques más preciados de la tierra. Resumo Florestas tropicais são os ecossistemas mais diversos e produtivos da Terra. Embora uma boa compreensão destas florestas seja crucial para o nosso futuro coletivo, até muito recentemente os esforços de medições e monitoramento foram amplamente desconexos. É essencial formarmos redes para obtermos respostas que transcendem fronteiras e horizontes de agências financiadoras. Neste estudo nós mostramos como uma comunidade global está respondendo aos desafios da pesquisa de ecossistemas tropicais, com equipes diversas medindo florestas, árvore por árvore, em milhares de parcelas monitoradas à longo prazo. Nós revisamos as maiores descobertas científicas deste trabalho, e mostramos também como este processo está mudando a ciência de florestas tropicais. Nossa abordagem principal envolve unir iniciativas de base a protocolos padronizados e gerenciamento de dados a fim de gerar resultados robustos em escalas ampliadas. Ao conectar pesquisadores tropicais e elevar seus status, nosso modelo de Rede de Pesquisa Social reconhece o papel-chave do produtor dos dados na descoberta científica. Concebida em 1999 com o RAINFOR (América do Sul), nossa rede de parcelas permanentes foi adaptada para África (AfriTRON) e Sudeste asiático (T-FORCES), e tem sido extensamente reproduzida em todo o mundo. Agora estas múltiplas iniciativas estão integradas através de uma infraestrutura cibernética do ForestPlots.net, conectando colegas de 54 países de 24 redes de parcelas. Estas iniciativas estão transformando coletivamente o entendimento das florestas tropicais e seus papéis na biosfera. Juntos nós descobrimos como, onde e por que o carbono e a biodiversidade da floresta estão respondendo às mudanças climáticas, e seus efeitos de retroalimentação. Esta duradoura colaboração pantropical revelou um grande sumidouro de carbono persistente e suas tendências, assim como tem evidenciado quais direcionadores são mais importantes, quais processos florestais são mais afetados, onde eles estão mudando, seus atrasos no tempo de resposta, e as prováveis respostas das florestas tropicais conforme o clima continua a mudar. Dessa forma, aproveitando uma notável tecnologia antiga, redes de parcelas acendem faíscas de uma moderna revolução na ciência das florestas tropicais. No futuro a humanidade pode se beneficiar incentivando estas comunidades basais que agora são coletivamente capazes de gerar conhecimentos únicos e duradouros sobre as florestas mais preciosas da Terra. Résume Les forêts tropicales sont les écosystèmes les plus diversifiés et les plus productifs de la planète. Si une meilleure compréhension de ces forêts est essentielle pour notre avenir collectif, jusqu'à tout récemment, les efforts déployés pour les mesurer et les surveiller ont été largement déconnectés. La mise en réseau est essentielle pour découvrir les réponses à des questions qui dépassent les frontières et les horizons des organismes de financement. Nous montrons ici comment une communauté mondiale relève les défis de la recherche sur les écosystèmes tropicaux avec diverses équipes qui mesurent les forêts arbre après arbre dans de milliers de parcelles permanentes. Nous passons en revue les principales découvertes scientifiques de ces travaux et montrons comment ce processus modifie la science des forêts tropicales. Notre approche principale consiste à relier les initiatives de base à long terme à des protocoles standardisés et une gestion de données afin de générer des résultats solides à grande échelle. En reliant les chercheurs tropicaux et en élevant leur statut, notre modèle de réseau de recherche sociale reconnaît le rôle clé de l'auteur des données dans la découverte scientifique. Conçus en 1999 avec RAINFOR (Amérique du Sud), nos réseaux de parcelles permanentes ont été adaptés à l'Afrique (AfriTRON) et à l'Asie du Sud-Est (T-FORCES) et largement imités dans le monde entier. Ces multiples initiatives sont désormais intégrées via l'infrastructure ForestPlots.net, qui relie des collègues de 54 pays à travers 24 réseaux de parcelles. Ensemble, elles transforment la compréhension des forêts tropicales et de leur rôle biosphérique. Ensemble, nous avons découvert comment, où et pourquoi le carbone forestier et la biodiversité réagissent au changement climatique, et comment ils y réagissent. Cette collaboration pan-tropicale à long terme a révélé un important puits de carbone à long terme et ses tendances, tout en mettant en évidence les facteurs les plus importants, les processus forestiers qui sont affectés, les endroits où ils changent, les décalages et les réactions futures probables des forêts tropicales à mesure que le climat continue de changer. En tirant parti d'une technologie remarquablement ancienne, les réseaux de parcelles déclenchent une révolution très moderne dans la science des forêts tropicales. À l'avenir, l'humanité pourra grandement bénéficier du soutien des communautés de base qui sont maintenant collectivement capables de générer une compréhension unique et à long terme des forêts les plus précieuses de la Terre. Abstrak Hutan tropika adalah di antara ekosistem yang paling produktif dan mempunyai kepelbagaian biodiversiti yang tinggi di seluruh dunia. Walaupun pemahaman mengenai hutan tropika amat penting untuk masa depan kita, usaha-usaha untuk mengkaji dan mengawas hutah-hutan tersebut baru sekarang menjadi lebih diperhubungkan. Perangkaian adalah sangat penting untuk mencari jawapan kepada soalan-soalan yang menjangkaui sempadan dan batasan agensi pendanaan. Di sini kami menunjukkan bagaimana sebuah komuniti global bertindak balas terhadap cabaran penyelidikan ekosistem tropika melalui penglibatan pelbagai kumpulan yang mengukur hutan secara pokok demi pokok dalam beribu-ribu plot jangka panjang. Kami meninjau semula penemuan saintifik utama daripada kerja ini dan menunjukkan bagaimana proses ini sedang mengubah bidang sains hutan tropika. Teras pendekatan kami memberi tumpuan terhadap penghubungan inisiatif akar umbi jangka panjang dengan protokol standar serta pengurusan data untuk mendapatkan hasil skala besar yang kukuh. Dengan menghubungkan penyelidik-penyelidik tropika dan meningkatkan status mereka, model Rangkaian Penyelidikan Sosial kami mengiktiraf kepentingan peranan pengasas data dalam penemuan saintifik. Bermula dengan pengasasan RAINFOR (Amerika Selatan) pada tahun 1999, rangkaian-rangkaian plot kekal kami kemudian disesuaikan untuk Afrika (AfriTRON) dan Asia Tenggara (T-FORCES) dan selanjutnya telah banyak dicontohi di seluruh dunia. Kini, inisiatif-inisiatif tersebut disepadukan melalui infrastruktur siber ForestPlots.net yang menghubungkan rakan sekerja dari 54 negara di 24 buah rangkaian plot. Secara kolektif, rangkaian ini sedang mengubah pemahaman tentang hutan tropika dan peranannya dalam biosfera. Kami telah bekerjasama untuk menemukan bagaimana, di mana dan mengapa karbon serta biodiversiti hutan bertindak balas terhadap perubahan iklim dan juga bagaimana mereka saling bermaklum balas. Kolaborasi pan-tropika jangka panjang ini telah mendedahkan sebuah sinki karbon jangka panjang serta arah alirannya dan juga menjelaskan pemandu-pemandu perubahan yang terpenting, di mana dan bagaimana proses hutan terjejas, masa susul yang ada dan kemungkinan tindakbalas hutan tropika pada perubahan iklim secara berterusan di masa depan. Dengan memanfaatkan pendekatan lama, rangkaian plot sedang menyalakan revolusi yang amat moden dalam sains hutan tropika. Pada masa akan datang, manusia sejagat akan banyak mendapat manfaat jika memupuk komuniti-komuniti akar umbi yang kini berkemampuan secara kolektif menghasilkan pemahaman unik dan jangka panjang mengenai hutan-hutan yang paling berharga di dunia

Modular Robot Systems From Self-Assembly to Self-Disassembly

We have presented a detailed retrospective on modular robots and discussed connections between modular robots and programmable matter. This field has seen a great deal of creativity and innovation at the level of designing physical systems capable of matching shape to function and algorithms that achieve this capability. The success of these projects rests on the convergence of innovation in hardware design and materials for creating the basic building blocks, information distribution for programming the interaction between the blocks, and control. Most current systems have dimensions on the order of centimeters, yet pack computation, communication, sensing, and power transfer capabilities into their form factors. Additionally, these modules operate using distributed algorithms that use a modules ability to observe its current neighborhood and local rules to decide what to do next.United States. Defense Advanced Research Projects Agency. Programmable Matter ProgramUnited States. Defense Advanced Research Projects Agency. Chembot ProgramUnited States. Army Research Office (grant W911NF-08-1-0228)United States. Army Research Office (grant W911NF-08-C-0060)National Science Foundation (U.S.). Office of Emerging Frontiers in Research and InnovationIntel CorporationNational Defense Science and Engineering Graduate Fellowshi

What's in the Bag: A Distributed Approach to 3D Shape Duplication with Modular Robots

Our goal is to develop an automated digital fabrication process that can make any object out of smart materials. In this paper, we present an algorithm for creating shapes by the process of duplication, using modules we have termed smart sand. The object to be duplicated is dipped into a bag of smart sand; the particles exchange messages to sense the object's shape; and then the particles selectively form mechanical bonds with their neighbors to form a duplicate of the original. Our algorithm is capable of duplicating convex and concave 3D objects in a completely distributed manner. It uses O(1) storage space and O(n) inter-module messages per module. We perform close to 500 experiments using a realistic simulator with over 1400 modules. These experiments confirm the functionality and messaging demands of our distributed duplication algorithm while demonstrating that the algorithm can be used to form interesting and useful shapes.US Army Research Office (Grant W911NF-08-1-0228)NSF (Grants 0735953 and 1138967

M-blocks: Momentum-driven, magnetic modular robots

In this paper, we describe a novel self-assembling, self-reconfiguring cubic robot that uses pivoting motions to change its intended geometry. Each individual module can pivot to move linearly on a substrate of stationary modules. The modules can use the same operation to perform convex and concave transitions to change planes. Each module can also move independently to traverse planar unstructured environments. The modules achieve these movements by quickly transferring angular momentum accumulated in a self-contained flywheel to the body of the robot. The system provides a simplified realization of the modular actions required by the sliding cube model using pivoting. We describe the principles, the unit-module hardware, and extensive experiments with a system of eight modules. Keywords: Actuators; Robots; Lattices; Hardware; Torque; Belts; FastenersNational Science Foundation (U.S.) (Grant 1240383)National Science Foundation (U.S.) (Grant 1138967

Robot pebbles: One centimeter modules for programmable matter through self-disassembly

This paper describes the design, fabrication, and experimental results of a programmable matter system capable of 2D shape formation through subtraction. The system is composed of autonomous 1cm modules which use custom-designed electropermanent magnets to bond, communicate, and share power with their neighbors. Given an initial block composed of many of these modules latched together in a regular crystalline structure, our system is able to form shapes by detaching the unnecessary modules. Many experiments show that the modules in our system are able to distribute data at 9600bps to their neighbors with a 98.5% success rate after four retries, and the connectors are able to support over 85 times the weight of a single module.United States. Army Research Office (grant number W911NF-08-1-0228)United States. Army Research Office (grant number W911NF-08-1-0254)Massachusetts Institute of Technology. Center for Bits and AtomsIntel CorporationNational Science Foundation (U.S.) ( EFRI grant)National Defense Science and Engineering Graduate FellowshipUnited States. Defense Advanced Research Projects Agency (DARPA Programmable Matter program