{"id":15070,"date":"2018-12-19T20:00:26","date_gmt":"2018-12-19T19:00:26","guid":{"rendered":"https:\/\/news.embl.de\/?p=15070"},"modified":"2024-03-22T12:06:26","modified_gmt":"2024-03-22T11:06:26","slug":"bio-inspired-shapes-robots","status":"publish","type":"post","link":"https:\/\/www.embl.org\/news\/science\/bio-inspired-shapes-robots\/","title":{"rendered":"Hundreds of tiny robots grow bio-inspired shapes"},"content":{"rendered":"\n<p>Hundreds of small robots can work in a team to create biology-inspired shapes \u2013 without an underlying master plan, purely based on local communication and movement. To achieve this, researchers from EMBL, CRG and Bristol Robotics Laboratory introduced the biological principles of self-organisation to swarm robotics. <em>Science Robotics<\/em> publishes the results on 19 December.<\/p>\n\n\n\n<p>\u201cWe show that it is possible to apply nature\u2019s concepts of self-organisation to human technology like robots,\u201d says EMBL Barcelona group leader James Sharpe. \u201cThat\u2019s fascinating because technology is very brittle compared to the robustness we see in biology. If one component of a car engine breaks down, it usually results in a non-functional car. By contrast when one element in a biological system fails, for example if a cell dies unexpectedly, it does not compromise the whole system, and will usually be replaced by another cell later. If we could achieve the same self-organisation and self-repair in technology, we can enable it to become much more useful than it is now.\u201d Sharpe led the project &#8211; initiated at the Centre for Genomic Regulation (CRG) &#8211; together with Sabine Hauert at the University of Bristol.<\/p>\n\n\n<div\n  class=\"vf-embed vf-embed--custom-ratio\"\n\n  style=\"--vf-embed-max-width: 100%;\n    --vf-embed-custom-ratio-x: 640;\n    --vf-embed-custom-ratio-y: 360;\"><iframe loading=\"lazy\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/dwA-ktc49t8\" frameborder=\"0\" allow=\"accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/div>\n\n\n\n<p class=\"vf-figure__caption\"> Shape formation as seen in the robot swarms. Complete experiments lasted for three and a half hours on average. Inspired by biology, robots store morphogens: virtual molecules that carry the patterning information. The colours signal the individual robots\u2019 morphogen concentration: green indicates very high morphogen values, blue and purple indicate lower values, and no colour indicates virtual absence of the morphogen in the robot. Each robot\u2019s morphogen concentration is broadcasted to neighbouring robots within a 10 centimetre range. The overall pattern of spots that emerges drives the relocation of robots to grow protrusions that reach out from the swarm. See a longer video: <a href=\"https:\/\/www.youtube.com\/watch?v=bEm-fXkLw7g&amp;feature=youtu.be\">https:\/\/youtu.be\/bEm-fXkLw7g<\/a>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Turing\u2019s rules<\/h2>\n\n\n\n<p>The only information that the team installed in the coin-sized robots were basic rules on how to interact with neighbours. In fact, they specifically programmed the robots in the swarm to act similarly to cells in a tissue. Those \u2019genetic\u2019 rules mimic the system responsible for the Turing patterns we see in nature, like the arrangement of fingers on a hand or the spots on a leopard. In this way, the project brings together two of Alan Turing\u2019s fascinations: computer science and pattern formation in biology.<\/p>\n\n\n\n<p>The robots rely on infrared messaging to communicate with neighbours within a 10 centimetre range. This makes the robots similar to biological cells, as they too can only directly communicate with other cells physically close to them.<\/p>\n\n\n\n<p>The swarm forms various shapes by relocating robots from areas with low morphogen concentration to areas with high morphogen concentration \u2013 called \u2018turing spots\u2019, which leads to the growth of protrusions reaching out from the swarm. \u201cIt\u2019s beautiful to watch the swarm grow into shapes, it looks quite organic. What\u2019s fascinating is there is no master plan, these shapes emerge as a result of simple interactions between the robots. This is different from previous work where the shapes were often predefined.\u201d says Sabine Hauert.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Working with large robot swarms<\/h2>\n\n\n\n<p>It is impossible to study swarm behaviour with just a couple of robots. That is why the team used at least three hundred in most experiments. Working with hundreds of tiny robots is a challenge in itself. They were able to do this thanks to a special setup which makes it easy to start and stop experiments, and reprogram all the robots at once using light. Over 20 experiments with large swarms were done, with each experiment taking around three and a half hours.<\/p>\n\n\n\n<p>Furthermore, just like in biology, things often go wrong. Robots get stuck, or trail away from the swarm in the wrong direction. \u201cThat\u2019s the kind of stuff that doesn\u2019t happen in simulations, but only when you do experiments in real life\u201d, says Ivica Slavkov, who shares first authorship of the paper with Daniel Carrillo-Zapata.<\/p>\n\n\n\n<p>All these details made the project challenging. The early part of the project was done in computer simulations, and it took the team about three years before the real robot swarm made its first shape. But the robots\u2019 limitations also forced the team to devise clever, robust mechanisms to orchestrate the swarm patterning. By taking inspiration from shape formation in biology, the team was able to show that their robot shapes could adapt to damage, and self-repair. The large-scale shape formation of the swarm is far more reliable than each of the little robots, the whole is greater than the sum of the parts.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Potential for real world applications<\/h2>\n\n\n\n<p>While inspiration was taken from nature to grow the swarm shapes, the goal is ultimately to make large robot swarms for real-world applications. Imagine hundreds or thousands of tiny robots growing shapes to explore a disaster environment after an earthquake or fire, or sculpting themselves into a dynamic 3D structure such as a temporary bridge that could automatically adjust its size and shape to fit any building or terrain. \u201cBecause we took inspiration from biological shape formation, which is known to be self-organised and robust to failure, such swarm could still keep working even some robots were damaged.\u201c says Daniel Carrillo-Zapata. There is still a long way to go however, before we see such swarms outside the laboratory.<\/p>\n\n\n\n<p><em>James Sharpe (EMBL Barcelona) led the Swarm-Organ project, which was initiated at the Centre for Genomic Regulation (CRG) when Sharpe was a group leader there. Sabine Hauert (Bristol Robotics Laboratory and University of Bristol) was the key senior collaborator. Other collaborators were Fredrik Jansson (currently employed at Centrum Wiskunde &amp; Informatica &#8211; CWI) and Jaap Kaandorp (University of Amsterdam &#8211; UvA).<\/em><\/p>\n\n\n\n<p><em>The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7) under grant agreement n\u00b0 601062, and the EPSRC Centre for Doctoral Training in Future Autonomous and Robotic Systems (FARSCOPE) at the Bristol Robotics Laboratory.<\/em><\/p>\n\n\n\n<hr class=\"vf-divider\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"es\">Crear formas biol\u00f3gicas con cientos de robots diminutos<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Cient\u00edficos del EMBL, el CRG y la Universidad de Bristol crean caracter\u00edsticas de autoorganizaci\u00f3n en enjambres de robots para estudiar la creaci\u00f3n de formas<\/h3>\n\n\n\n<p>Cientos de peque\u00f1os robots pueden trabajar en equipo para crear formas de tipo biol\u00f3gico, sin un plan maestro subyacente, bas\u00e1ndose puramente en la comunicaci\u00f3n mutua y el movimiento. Para lograrlo, los investigadores introdujeron los principios biol\u00f3gicos de autoorganizaci\u00f3n en la rob\u00f3tica de enjambre.&nbsp;<em>Science Robotics<\/em>&nbsp;publica los resultados el 19 de diciembre.<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"vf-figure  | vf-figure--align vf-figure--align-centered  size-large\"><img decoding=\"async\" class=\"vf-figure__image\" src=\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2018\/12\/robots-ib.jpg\" alt=\"\"\/><figcaption class=\"vf-figure__caption\">Los robots utilizados en los experimentos. La forma de este enjambre en concreto es meramente una ilustraci\u00f3n de la t\u00e9cnica, no fue creado por los robots. FOTO: reimpresa con permiso de AAAS.<\/figcaption><\/figure><\/div>\n\n\n\n<p>&#8220;Demostramos que es posible aplicar los conceptos de autoorganizaci\u00f3n de la naturaleza a la tecnolog\u00eda humana como los robots&#8221;, dice el l\u00edder del grupo del EMBL Barcelona, James Sharpe. &#8220;Esto es fascinante porque la tecnolog\u00eda es muy fr\u00e1gil en comparaci\u00f3n con la robustez que vemos en la biolog\u00eda. Si un componente del motor de un coche se aver\u00eda, normalmente da como resultado un coche que no funciona. En cambio, cuando un elemento de un sistema biol\u00f3gico falla, por ejemplo, si una c\u00e9lula muere repentinamente, no compromete todo el sistema. Y podr\u00eda incluso ser reemplazada por otra c\u00e9lula posteriormente. Si pudi\u00e9ramos lograr la misma tecnolog\u00eda de auto organizaci\u00f3n y auto reparaci\u00f3n, podr\u00edamos conseguir que fuera mucho m\u00e1s potente de lo que es ahora&#8221;. Sharpe dirigi\u00f3 el proyecto, iniciado en el Centro de Regulaci\u00f3n Gen\u00f3mica (CRG), junto con Sabine Hauert de la Universidad de Bristol.<\/p>\n\n\n<div\n  class=\"vf-embed vf-embed--custom-ratio\"\n\n  style=\"--vf-embed-max-width: 100%;\n    --vf-embed-custom-ratio-x: 640;\n    --vf-embed-custom-ratio-y: 360;\"><iframe loading=\"lazy\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/dwA-ktc49t8\" frameborder=\"0\" allow=\"accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/div>\n\n\n\n<p class=\"vf-figure__caption\">Creaci\u00f3n de formas como se ve en los enjambres de robots. Cada v\u00eddeo se acelera unas 100 veces. Los colores se\u00f1alan la concentraci\u00f3n morf\u00f3gena del robot individual: verde indica valores morf\u00f3genos muy altos, azul y p\u00farpura indican valores m\u00e1s bajos, y sin color indica ausencia virtual de morf\u00f3geno en el robot. Los morf\u00f3genos son las mol\u00e9culas que llevan la informaci\u00f3n de la generaci\u00f3n de patrones en los sistemas biol\u00f3gicos. Estos son imitados en los robots. La concentraci\u00f3n de morf\u00f3genos en cada robot es transmitida a los robots vecinos en un radio de 10 cent\u00edmetros. La forma del enjambre es impulsada por los valores del morf\u00f3geno y el patr\u00f3n general. <a href=\"https:\/\/www.youtube.com\/watch?v=bEm-fXkLw7g&amp;feature=youtu.be\">https:\/\/youtu.be\/bEm-fXkLw7g<\/a><br \/>Video:&nbsp;reimpresa con permiso de&nbsp;Slavkov, I., Zapata D. C. et al., Science Robotics (2018).<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Reglas de Turing<\/h2>\n\n\n\n<p>La \u00fanica informaci\u00f3n que el equipo instal\u00f3 en los robots &#8211; que tienen el tama\u00f1o de una moneda &#8211; fueron reglas b\u00e1sicas sobre c\u00f3mo interactuar con los vecinos. De hecho, programaron los robots espec\u00edficamente en un enjambre para actuar como las c\u00e9lulas en un tejido. Estas reglas &#8220;gen\u00e9ticas&#8221; imitan el sistema responsable de los patrones de Turing que vemos en la naturaleza, como la organizaci\u00f3n de los dedos en una mano o las manchas de un leopardo. De esta manera, el proyecto re\u00fane dos de las fascinaciones de Alan Turing: la inform\u00e1tica y la formaci\u00f3n de patrones en la biolog\u00eda.<\/p>\n\n\n\n<p>Los robots se comunican con los vecinos por infrarrojos en un radio de 10 cent\u00edmetros. Esto hace que los robots sean similares a las c\u00e9lulas biol\u00f3gicas, ya que estas tambi\u00e9n se comunican directamente solo con otras c\u00e9lulas pr\u00f3ximas f\u00edsicamente.<\/p>\n\n\n\n<p>El enjambre es capaz de crear varias formas trasladando robots de zonas con baja concentraci\u00f3n de morf\u00f3genos a zonas con una alta concentraci\u00f3n \u2013 llamadas \u201cc\u00edrculos Turing\u201d &#8211; hecho que lleva a crear tent\u00e1culos en el enjambre de robots. \u201cEs fant\u00e1stico ver c\u00f3mo el robot crea diferentes formas. Parece un proceso org\u00e1nico. Lo que es m\u00e1s fascinante es que no hay un plan preestablecido, las formas surgen como resultado de las interacciones entre los robots. Esto diferencia nuestro trabajo de investigaciones anteriores, donde a menudo las formas estaban predefinidas.\u201d comenta Sabine Hauert.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Trabajar con grandes enjambres de robots<\/h2>\n\n\n\n<p>Es imposible estudiar el comportamiento de un enjambre con solo un par de robots. Por eso el equipo utiliz\u00f3 al menos trescientos en la mayor\u00eda de los experimentos. Trabajar con cientos de robots diminutos es un reto en s\u00ed mismo. El equipo de investigaci\u00f3n lo llevo a cabo utilizando un m\u00e9todo que facilita iniciar y detener el experimento, as\u00ed como reprogramar todos los robots a la vez utilizando luz. En total se realizaron unos 20 experimentos con un gran n\u00famero de robots, con una duraci\u00f3n aproximada de 3 horas por experimento.<br \/>Es m\u00e1s, al igual que en la biolog\u00eda, a veces las cosas salen mal. Como las c\u00e9lulas, los robots se quedan atascados, o se separan del enjambre en la direcci\u00f3n equivocada. &#8220;Este es el tipo de cosas que no pasan en las simulaciones, sino cuando realizas los experimentos en la vida real&#8221;, comenta Ivica Slavkov, que comparte la primera autor\u00eda del art\u00edculo con Daniel Carrillo-Zapata. &#8220;Se podr\u00eda decir que los robots son temperamentales. Rinden mejor por la ma\u00f1ana que por la noche, por ejemplo. Esto es porque las condiciones de iluminaci\u00f3n son \u00f3ptimas para su sistema de comunicaci\u00f3n en ese momento&#8221;.<\/p>\n\n\n\n<p>Todos estos detalles hicieron que el proyecto fuera un gran reto. La primera parte se realiz\u00f3 con simulaciones por ordenador y pasaron tres a\u00f1os hasta el enjambre de robots reales crearon la primera estructura. Las limitaciones de los robots tambi\u00e9n forzaron al equipo a que concibiera mecanismos s\u00f3lidos e inteligentes para orquestar la generaci\u00f3n de patrones del enjambre. Y eso hace que los enjambres de robots sean m\u00e1s parecidos a la biolog\u00eda real. La creaci\u00f3n de formas a gran escala del enjambre es mucho m\u00e1s fiable que cada uno de los peque\u00f1os robots por separado: el conjunto es mayor que la suma de las partes.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Potencial para uso en el mundo real<\/h2>\n\n\n\n<p>Aunque la inspiraci\u00f3n del proyecto surgi\u00f3 de la naturaleza, el objetivo final es crear enjambres de robots para usarlos en el mundo real. Imagina cientos o miles de peque\u00f1os robots creando formas o esculpiendo estructuras din\u00e1micas en 3D que se adapten a cualquier tama\u00f1o y terreno. Por ejemplo, un puente de miles de robots despu\u00e9s de un se\u00edsmo. \u201cComo nos inspiramos en la creaci\u00f3n de formas de la biolog\u00eda, en la que existe una auto organizaci\u00f3n y es resistente a los posibles fallos, los robots podr\u00edan seguir funcionando, aunque algunos de ellos estuviesen da\u00f1ados.\u201d dice Daniel Carrillo-Zapata. Aun as\u00ed, hay un largo camino por recorrer antes que los enjambres de robots salgan del laboratorio.<\/p>\n\n\n\n<p><em>James Sharpe (EMBL Barcelona) dirigi\u00f3 el proyecto Swarm-Organ, que se inici\u00f3 en el Centro de Regulaci\u00f3n Gen\u00f3mica (CRG) cuando Sharpe era l\u00edder de grupo all\u00ed. Sabine Hauert (Universidad de Bristol) era la colaboradora veterana clave. Otros colaboradores fueron Fredrik Jansson (empleado actualmente en el Centrum Wiskunde &amp; Informatica &#8211; CWI) y Jaap Kaandorp (Universidad de Amsterdam &#8211; UvA).<\/em><\/p>\n\n\n\n<p><em>La investigaci\u00f3n que dio pie a estos resultados recibi\u00f3 fondos del European Union Seventh Framework Programme (FP7) bajo el acuerdo de beca n\u00b0 601062 y el EPSRC Centre for Doctoral Training in Future Autonomous and Robotic Systems (FARSCOPE) en el Bristol Robotics Laboratory.<\/em><\/p>\n\n\n\n<hr class=\"vf-divider\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"ct\">Creant estructures inspirades en la biol\u00f2gia amb centenars de petits robots<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Cient\u00edfics de l\u2019EMBL, del CRG i de la Universitat de Bristol programen un eixam de robots amb principis d\u2019auto-organitzaci\u00f3 per estudiar la formaci\u00f3 de patrons<\/h3>\n\n\n\n<p>Centenars de petits robots poden treballar en equip per crear estructures semblants a les biol\u00f2giques sense un pla mestre subjacent, sin\u00f3 purament basats en comunicaci\u00f3 amb robots ve\u00efns i moviment. Per aconseguir-ho, els investigadors han introdu\u00eft principis biol\u00f2gics d\u2019auto-organitzaci\u00f3 a un eixam de robots.&nbsp;<em>Science Robotics<\/em>&nbsp;en publica els resultats el 19 de desembre.<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"vf-figure  | vf-figure--align vf-figure--align-centered  size-large\"><img decoding=\"async\" class=\"vf-figure__image\" src=\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2018\/12\/robots-ib.jpg\" alt=\"\"\/><figcaption class=\"vf-figure__caption\">Els robots utilitzats durant els experiments. L\u2019estructura d\u2019aquest eixam \u00e9s nom\u00e9s una il\u00b7lustraci\u00f3 de la t\u00e8cnica. FOTO: reimpresa amb perm\u00eds de AAAS.<\/figcaption><\/figure><\/div>\n\n\n\n<p>\u201cMostrem que \u00e9s possible aplicar els conceptes naturals d\u2019auto-organitzaci\u00f3 a la tecnologia humana, com ara als robots,\u201d diu James Sharpe, el cap de grup de l\u2019EMBL Barcelona. \u201c\u00c9s fascinant, perqu\u00e8 la tecnologia \u00e9s molt fr\u00e0gil comparada amb la robustesa de la biologia. Si un component del motor d\u2019un cotxe s\u2019espatlla, en general acaba causant que el cotxe no funcioni. En canvi, quan un element d\u2019un sistema natural falla, per exemple si una c\u00e8l\u00b7lula mor de sobte, no posa en perill el sistema sencer. Fins i tot la podria substituir una altra c\u00e8l\u00b7lula m\u00e9s endavant. Si pogu\u00e9ssim aconseguir la mateixa auto-organitzaci\u00f3 i auto-reparaci\u00f3 a la tecnologia, podr\u00edem fer-la molt m\u00e9s poderosa del que ja \u00e9s.\u201d Sharpe va liderar el projecte, que es va iniciar al Centre de Regulaci\u00f3 Gen\u00f2mica (CRG) juntament amb Sabine Hauert de la Universitat de Bristol.<\/p>\n\n\n<div\n  class=\"vf-embed vf-embed--custom-ratio\"\n\n  style=\"--vf-embed-max-width: 100%;\n    --vf-embed-custom-ratio-x: 640;\n    --vf-embed-custom-ratio-y: 360;\"><iframe loading=\"lazy\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/dwA-ktc49t8\" frameborder=\"0\" allow=\"accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/div>\n\n\n\n<p class=\"vf-figure__caption\">La formaci\u00f3 d\u2019estructures tal com s\u2019observa en l\u2019eixam de robots. La llargada dels experiments \u00e9s de tres hores de mitjana. Inspirat en la biologia, els robots emmagatzemen morf\u00f2gens: mol\u00e8cules virtuals que transmeten informaci\u00f3 del patr\u00f3. Els colors indiquen la concentraci\u00f3 de morfogen de cada robot xx: verd indica valors de morfogen alts, blau i lila indiquen valors m\u00e9s baixos i l\u2019abs\u00e8ncia de color indica l\u2019abs\u00e8ncia de morfogen en el robot. Cada robot emet la seva concentraci\u00f3 de morf\u00f2gen als robots en un radi de 10 cent\u00edmetres. El patr\u00f3 de cercles d\u2019alta concentraci\u00f3 de morfogen dirigeix la relocalitzaci\u00f3 de robots i el creixement de tentacles que emergeixen de l\u2019eixam. <a href=\"https:\/\/youtu.be\/bEm-fXkLw7g\">https:\/\/youtu.be\/bEm-fXkLw7g<\/a><br \/>Video:&nbsp;reimpresa amb perm\u00eds de&nbsp;Slavkov, I., Zapata D. C. et al., Science Robotics (2018).<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Les regles de Turing<\/h2>\n\n\n\n<p>L\u2019\u00fanica informaci\u00f3 que l\u2019equip ha introdu\u00eft en els robots, que fan la mida d\u2019una moneda aproximadament, s\u00f3n regles b\u00e0siques sobre com interactuar amb els ve\u00efns. De fet, han programat els robots en l\u2019eixam perqu\u00e8 es comportin com c\u00e8l\u00b7lules d\u2019un teixit. Aquestes regles \u201cgen\u00e8tiques\u201d imiten el sistema que s\u2019encarrega dels patrons de Turing que veiem a la natura, com ara la disposici\u00f3 dels dits en una m\u00e0 o la taques d\u2019un lleopard. D\u2019aquesta manera, el projecte reuneix dues de les passions d\u2019Alan Turing: la ci\u00e8ncia computacional i la formaci\u00f3 de patrons biol\u00f2gics.<\/p>\n\n\n\n<p>Els robots es comuniquen mitjan\u00e7ant missatges transmesos per infrarojos amb els robots que es troben a dins d\u2019un radi de 10 cent\u00edmetres. Aix\u00f2 fa que s\u2019assemblin a les c\u00e8l\u00b7lules biol\u00f2giques, perqu\u00e8 aquestes nom\u00e9s poden comunicar-se directament amb altres c\u00e8l\u00b7lules que estiguin f\u00edsicament a prop.<\/p>\n\n\n\n<p>L\u2019 eixam adopta diverses formes a mida que els robots es mouen de regions de baixa a alta concentraci\u00f3 de morfogen, anomenats cercles de Turing. \u201c\u00c9s captivador observar l\u2019eixam crear formes, sembla un proc\u00e9s org\u00e0nic. El que \u00e9s fascinant \u00e9s que no hi ha un pla mestre, aquestes formes emergeixen d\u2019interaccions simples entre els robots. Aquesta \u00e9s una difer\u00e8ncia important amb estudis previs, on les formes sovint eren predefinides.\u201c explica Sabine Hauert.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Treballar amb grans eixams de robots<\/h2>\n\n\n\n<p>\u00c9s impossible estudiar el comportament d\u2019un eixam amb nom\u00e9s un parell de robots. Per aix\u00f2, l\u2019equip n\u2019ha utilitzat almenys tres-cents en la majoria d\u2019experiments. Treballar amb centenars de petits robots ja \u00e9s un repte en si. L\u2019equip d\u2019investigadors van poder dur-ho a terme fent servir un m\u00e8tode que facilita comen\u00e7ar i parar els experiments o reprogramar tots els robots alhora fent servir llum. En total es van realitzar uns 20 experiments amb un gran nombre de robots, amb una durada aproximada de 3 hores per experiment.<\/p>\n\n\n\n<p>Com en la biologia, un experiment sovint surt malament. Igual que les c\u00e8l\u00b7lules, els robots poden encallar o perdre l\u2019eixam. \u201cS\u00f3n la mena de coses que no passen a les simulacions, sin\u00f3 nom\u00e9s en veritables experiments\u201d diu Ivica Slavkov, l\u2019autor principal de l\u2019article junt amb Daniel Carrillo-Zapata.<\/p>\n\n\n\n<p>Tots aquests detalls han fet que aquest projecte fos un gran repte. La primera part es va realitzar fent simulacions per ordinador i van passar tres anys fins que un eixam de robots reals va crear la primera estructura. Les limitacions dels robots, per\u00f2, tamb\u00e9 van obligar l\u2019equip a dissenyar mecanismes intel\u00b7ligents i robustos per orquestrar la formaci\u00f3 de patrons de l\u2019eixam. Inspirant-se en processos de creaci\u00f3 de formes biol\u00f2giques, l\u2019equip va poder demostrar que les estructures creades pels robots podien adaptar-se a danys externs i auto-reparar-se. D\u2019aquest manera, la formaci\u00f3 d\u2019estructures a gran escala de l\u2019eixam \u00e9s molt m\u00e9s robusta que cada un dels petits robots, \u00e9s a dir, el conjunt \u00e9s m\u00e9s que la suma de les parts.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Potencial per aplicacions en el m\u00f3n real<\/h2>\n\n\n\n<p>Encara que la inspiraci\u00f3 del projecte sorg\u00eds de la natura, l\u2019objectiu a llarg termini \u00e9s utilitzar grans eixams de robots per aplicacions en el mon real. Imagina centenars o milers de robots diminuts creant estructures per explorar l\u2019escenari d\u2019una cat\u00e0strofe despr\u00e9s d\u2019un terratr\u00e8mol o un incendi, construint estructures din\u00e0miques 3D com per exemple un pont que pogu\u00e9s adaptar la seva llargada i forma per encaixar en diferents terreny o edificis. \u201cCom ens vam inspirar en la formaci\u00f3 de patrons biol\u00f2gics, que es caracteritza per l\u2019auto-organitzaci\u00f3 i robustesa, els robots podrien seguir funcionant, encara que alguns estiguessin danyats.\u201d explica Daniel Carrillo-Zapata. Tot i aix\u00ed, hi ha un llarg cam\u00ed per rec\u00f3rrer abans que els eixams de robot surtin del laboratori.<\/p>\n\n\n\n<p><em>James Sharpe (EMBL Barcelona) va encap\u00e7alar el projecte Swarm-Organ, iniciat al Centre de Regulaci\u00f3 Gen\u00f2mica (CRG) quan Sharpe n\u2019era un l\u00edder de grup. Sabine Hauert (Universitat de Bristol) va ser la col\u00b7laboradora s\u00e8nior clau. Tamb\u00e9 van col\u00b7laborar Fredrik Jansson (actualment treballa a Centrum Wiskunde &amp; Informatica &#8211; CWI) i Jaap Kaandorp (Universitat d\u2019Amsterdam &#8211; UvA).<\/em><\/p>\n\n\n\n<p><em>The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7) under grant agreement n\u00b0 601062, i el EPSRC Centre for Doctoral Training in Future Autonomous and Robotic Systems (FARSCOPE) al Bristol Robotics Laboratory.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Scientists build self-organising features into robot swarms to study shape formation<\/p>\n","protected":false},"author":58,"featured_media":15071,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[2,17591],"tags":[497,643,647,1748,754,759,760,500,648],"embl_taxonomy":[19377],"class_list":["post-15070","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-science","category-science-technology","tag-barcelona","tag-morphogenesis","tag-pattern-formation","tag-press-release","tag-robot","tag-self-organisation","tag-shape-formation","tag-sharpe","tag-turing","embl_taxonomy-sharpe-group"],"acf":{"article_intro":"<p>Scientists build self-organising features into robot swarms to study shape formation<\/p>\n","related_links":[{"link_description":"Research of the Sharpe group at EMBL Barcelona ","link_url":"https:\/\/www.embl.es\/research\/unit\/sharpe\/"},{"link_description":"Research of the Hauert lab at the University of Bristol","link_url":"http:\/\/hauertlab.com\/"},{"link_description":"More about the CRG ","link_url":"https:\/\/www.crg.eu\/"},{"link_description":"More about the Swarm-Organ project ","link_url":"https:\/\/www.swarm-organ.eu\/"},{"link_description":"James Sharpe explaining the Swarm-Organ project when it had just been initiated in 2013","link_url":"https:\/\/www.theguardian.com\/media-network\/media-network-blog\/video\/2013\/jul\/25\/activate-2013-james-sharpe"}],"article_sources":[{"source_description":"<p>Slavkov, I., Zapata D. C. <em>et al<\/em>. Morphogenesis in robot swarms. <em>Science Robotics<\/em>, published online on 19 December 2018. DOI: 10.1126\/scirobotics.aau9178<\/p>\n","source_link_url":"http:\/\/robotics.sciencemag.org\/content\/3\/25\/eaau9178"}],"vf_locked":false,"featured":false,"color":"#007B53","link_color":"#fff","show_featured_image":false,"in_this_article":false,"youtube_url":"","mp4_url":"","video_caption":"","translations":[{"translation_language":"Catalan","translation_anchor":"#es"},{"translation_language":"Catalan","translation_anchor":"#ct"}],"press_contact":"EMBL Generic"},"embl_taxonomy_terms":[{"uuid":"a:3:{i:0;s:36:\"302cfdf7-365b-462a-be65-82c7b783ebf7\";i:1;s:36:\"18a7a17b-e276-4afd-b0ca-8ddac1883d45\";i:2;s:36:\"6c31c788-04a1-48b8-a532-fdc251506b57\";}","parents":[],"name":["Sharpe Group"],"slug":"sharpe-group","description":"What &gt; Tissue biology and disease modelling &gt; Sharpe Group"}],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Hundreds of tiny robots grow bio-inspired shapes | EMBL<\/title>\n<meta name=\"description\" content=\"Scientists build self-organising features into robot swarms to study shape formation\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.embl.org\/news\/science\/bio-inspired-shapes-robots\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Hundreds of tiny robots grow bio-inspired shapes | EMBL\" \/>\n<meta property=\"og:description\" content=\"Scientists build self-organising features into robot swarms to study shape formation\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.embl.org\/news\/science\/bio-inspired-shapes-robots\/\" \/>\n<meta property=\"og:site_name\" content=\"EMBL\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/embl.org\/\" \/>\n<meta property=\"article:published_time\" content=\"2018-12-19T19:00:26+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-03-22T11:06:26+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2018\/12\/robots-ib.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"620\" \/>\n\t<meta property=\"og:image:height\" content=\"425\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Iris Kruijen\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@IrisKruijen\" \/>\n<meta name=\"twitter:site\" content=\"@embl\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Iris Kruijen\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"17 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"NewsArticle\",\"@id\":\"https:\/\/www.embl.org\/news\/science\/bio-inspired-shapes-robots\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/bio-inspired-shapes-robots\/\"},\"author\":{\"name\":\"Iris Kruijen\",\"@id\":\"https:\/\/www.embl.org\/news\/#\/schema\/person\/bdd9b4c648f9ed37311c369a20ac77e1\"},\"headline\":\"Hundreds of tiny robots grow bio-inspired shapes\",\"datePublished\":\"2018-12-19T19:00:26+00:00\",\"dateModified\":\"2024-03-22T11:06:26+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/bio-inspired-shapes-robots\/\"},\"wordCount\":3442,\"publisher\":{\"@id\":\"https:\/\/www.embl.org\/news\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/bio-inspired-shapes-robots\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2018\/12\/robots-ib.jpg\",\"keywords\":[\"barcelona\",\"morphogenesis\",\"pattern formation\",\"press release\",\"robot\",\"self-organisation\",\"shape formation\",\"sharpe\",\"turing\"],\"articleSection\":[\"Science\",\"Science &amp; 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