000150468 001__ 150468
000150468 005__ 20180501105940.0
000150468 0247_ $$2doi$$a10.5075/epfl-thesis-4803
000150468 02470 $$2urn$$aurn:nbn:ch:bel-epfl-thesis4803-1
000150468 02471 $$2nebis$$a6125597
000150468 037__ $$aTHESIS_LIB
000150468 041__ $$aeng
000150468 088__ $$a4803
000150468 245__ $$aRoombots: Design and Implementation of a Modular Robot for Reconfiguration and Locomotion
000150468 269__ $$a2010
000150468 260__ $$aLausanne$$bEPFL$$c2010
000150468 300__ $$a187
000150468 336__ $$aTheses
000150468 520__ $$aIn this thesis we present the design and implementation of       a novel self-reconfiguring modular (SR-MR) robotic system:       Roombots. We are aiming at three main applications with       Roombots; locomotion through self-reconfiguration in the       regular cubic 3D-lattice on structured surfaces, locomotion       in non-structured environments applying central pattern       generators (CPG) as the locomotion controller, and       self-assembly and reconfiguration of static objects of the       day-to-day environment, such as furniture. Robot assemblies from self-reconfigurable modular robots       have the ability to adapt to a given task and working       environment by altering their shape through a series of       reconfiguration moves, and attachments and detachments       between the modules. We are interested in self-reconfiguring modular robots for       their shape-changing capabilities, and their distributed       characteristics. We envision the following applications for       Roombots: First, self-reconfiguration in a structured 3D       lattice, i.e. a floor and walls equipped with connectors.       Embedded connectors can provide pivot points for locomotion       of SR-MR assemblies, and docking and recharging places for       our adaptive furniture pieces. Second, our proposed concept       for locomotion control of modular robots on non-structured       ground are central pattern generators. Third, we would like       to build adaptive and versatile furniture from modular robots       and light-weight elements. In the following we are able to count more than 60 modular       robotic systems, developed over the last two decades. However       we were unable to identify an existing system which could       provide us with all desired kinematic and geometric       capabilities. This led us to design and implement a novel       self-reconfiguring modular robotic system: Roombots. To tackle the module design we attempt to identify both       meaningful design parameters from existing modular robots,       and essential features for our applications. The combination       of both leads to the kinematic and geometric description of       the Roombots modules, and eventually to its       implementation. In order to be able to assemble furniture from our       Roombots units in the future, we need a reconfiguration       framework which supports the specific requirements of       Roombots. Metamodules made of two units attached in-series       are attracted and guided by a virtual force-field, they use       broadcast signals, look-up tables of collision clouds and       simple assumptions about their near environment to reach       their seeding positions, which are currently hand coded. For the task of locomotion in non-structured environments       we propose a framework for learning to move with modular       robots using central pattern generators and online       optimization. The distributed implementation of CPGs offers       an ideal substrate for producing locomotion patterns and for       online learning, and an optimization framework for fast       learning.
000150468 6531_ $$aself-reconfiguring modular robots
000150468 6531_ $$acentral pattern generators
000150468 6531_ $$aactive connection mechanism
000150468 6531_ $$alocomotion through reconfiguration
000150468 6531_ $$aadaptive robotic furniture
000150468 6531_ $$aonline optimization
000150468 700__ $$0240378$$aSpröwitz, Alexander$$g173229
000150468 720_2 $$0241344$$aIjspeert, Auke Jan$$edir.$$g115955
000150468 8564_ $$s53768815$$uhttps://infoscience.epfl.ch/record/150468/files/EPFL_TH4803.pdf$$yTexte intégral / Full text$$zTexte intégral / Full text
000150468 909C0 $$0252049$$pBIOROB$$xU12165
000150468 909CO $$ooai:infoscience.tind.io:150468$$pDOI$$pthesis$$pthesis-bn2018$$pDOI2$$pSTI
000150468 918__ $$aSTI$$cIBI-STI$$dEDPR
000150468 919__ $$aBIOROB
000150468 920__ $$b2010
000150468 970__ $$a4803/THESES
000150468 973__ $$aEPFL$$sPUBLISHED
000150468 980__ $$aTHESIS