@book{20182, author = {{Hamann, Heiko}}, publisher = {{Springer}}, title = {{{Space-Time Continuous Models of Swarm Robotics Systems: Supporting Global-to-Local Programming}}}, doi = {{10.1007/978-3-642-13377-0}}, year = {{2010}}, } @inproceedings{20220, author = {{Hamann, Heiko and Schmickl, Thomas and Stradner, Jürgen and Crailsheim, Karl}}, booktitle = {{Proceedings of the IEEE Congress on Evolutionary Computation (CEC'10)}}, pages = {{244----251}}, title = {{{A Hormone-Based Controller for Evolutionary Multi-Modular Robotics: From Single Modules to Gait Learning}}}, doi = {{10.1109/CEC.2010.5585994}}, year = {{2010}}, } @inproceedings{20222, author = {{Schmickl, Thomas and Hamann, Heiko and Stradner, Jürgen and Mayet, Ralf and Crailsheim, Karl}}, booktitle = {{Proc. of the ALife XII Conference}}, pages = {{648----655}}, publisher = {{MIT Press}}, title = {{{Complex Taxis-Behaviour in a Novel Bio-Inspired Robot Controller}}}, year = {{2010}}, } @inproceedings{20223, abstract = {{The semi-automatic or automatic synthesis of robot controller software is both desirable and challenging. Synthesis of rather simple behaviors such as collision avoidance by applying artificial evolution has been shown multiple times. However, the difficulty of this synthesis increases heavily with increasing complexity of the task that should be performed by the robot. We try to tackle this problem of complexity with Artificial Homeostatic Hormone Systems (AHHS), which provide both intrinsic, homeostatic processes and (transient) intrinsic, variant behavior. By using AHHS the need for pre-defined controller topologies or information about the field of application is minimized. We investigate how the principle design of the controller and the hormone network size affects the overall performance of the artificial evolution (i.e., evolvability). This is done by comparing two variants of AHHS that show different effects when mutated. We evolve a controller for a robot built from five autonomous, cooperating modules. The desired behavior is a form of gait resulting in fast locomotion by using the modules' main hinges.}}, author = {{Hamann, Heiko and Stradner, Jürgen and Schmickl, Thomas and Crailsheim, Karl}}, booktitle = {{Artificial Life XII (ALife XII), Odense, Denmark}}, pages = {{773--780}}, publisher = {{MIT Press}}, title = {{{Artificial Hormone Reaction Networks: Towards Higher Evolvability in Evolutionary Multi-Modular Robotics}}}, year = {{2010}}, } @inproceedings{20226, author = {{Hamann, Heiko and Meyer, Bernd and Schmickl, Thomas and Crailsheim, Karl}}, booktitle = {{From Animals to Animats 11}}, isbn = {{9783642151927}}, issn = {{0302-9743}}, pages = {{639--648}}, publisher = {{Springer}}, title = {{{A Model of Symmetry Breaking in Collective Decision-Making}}}, doi = {{10.1007/978-3-642-15193-4_60}}, volume = {{6226}}, year = {{2010}}, } @inproceedings{20258, abstract = {{Self-organization in natural systems demonstrates very reliable and scalable collective behavior without using any central elements. When providing collective robotic systems with self-organizing principles, we are facing new problems of making self-organization purposeful, self-adapting to changing environments and faster, in order to meet requirements from a technical perspective. This paper describes on-going work of creating such an artificial self-organization within artificial robot organisms, performed in the framework of several European projects.}}, author = {{Kernbach, Serge and Hamann, Heiko and Stradner, Jürgen and Thenius, Ronald and Schmickl, Thomas and Crailsheim, Karl and Rossum, A.C. van and Sebag, Michele and Bredeche, Nicolas and Yao, Yao and Baele, Guy and Peer, Yves Van de and Timmis, Jon and Mohktar, Maizura and Tyrrell, Andy and Eiben, A.E. and McKibbin, S.P. and Liu, Wenguo and Winfield, Alan F.T.}}, booktitle = {{2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns}}, isbn = {{9781424451661}}, title = {{{On Adaptive Self-Organization in Artificial Robot Organisms}}}, doi = {{10.1109/computationworld.2009.9}}, year = {{2010}}, } @inbook{18761, author = {{Hamann, Heiko and Schmickl, Thomas and Stradner, Jürgen and Crailsheim, Karl and Levi, Paul and Kernbach, Serge}}, booktitle = {{Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution}}, pages = {{240----263}}, publisher = {{Springer}}, title = {{{Hormone-based Control for Multi-modular Robotics}}}, year = {{2010}}, } @inproceedings{19023, author = {{Kernbach, Serge and Schmickl, Thomas and Hamann, Heiko and Stradner, Jürgen and Schlachter, Florian and Schwarzer, Christopher s. F. and Winfield, Alan F. T. and Matthias, Rene}}, booktitle = {{Artificial Life XII (ALife XII)}}, pages = {{781--788}}, publisher = {{MIT Press}}, title = {{{Adaptive Action Selection Mechanisms for Evolutionary Multimodular Robotics}}}, year = {{2010}}, } @inproceedings{20254, abstract = {{One of the prominent challenges in mobile robotics is to develop control methodologies that allow the adaptation to dynamic and unforeseen environments. The classic approach of hand-coded controllers is very efficient for well-defined tasks and specific environments but poor in adapting to changing environmental conditions. One alternative approach is the application of evolutionary algorithms which need, in turn, easily evolvable representations of controllers. In this paper, we investigate one promising approach of an artificial hormone system as a control paradigm which is believed to be easily optimized by evolutionary processes. In a first step of this research, we focus on the simple task of collision avoidance. We present a brief mathematical analysis of this controller approach and an implementation of the controller on a mobile robot to check the feasibility in principle of our approach. The task is successfully accomplished and we conclude with a discussion of the hormone dynamics in the robot.}}, author = {{Stradner, Jürgen and Hamann, Heiko and Schmickl, Thomas and Crailsheim, Karl}}, booktitle = {{2009 IEEE/RSJ International Conference on Intelligent Robots and Systems}}, isbn = {{9781424438037}}, title = {{{Analysis and implementation of an Artificial Homeostatic Hormone System: A first case study in robotic hardware}}}, doi = {{10.1109/iros.2009.5354056}}, year = {{2009}}, } @article{20255, abstract = {{By compiling macroscopic models we analyze the adaptive behavior in a swarm of autonomous robots generated by a bio-inspired, distributed control algorithm. We developed two macroscopic models by taking two different perspectives: A Stock & Flow model, which is simple to implement and fast to simulate, and a spatially resolved model based on diffusion processes. These two models were compared concerning their prediction quality and their analytical power: One model allowed easy identification of the major feedback loops governing the swarm behavior. The other model allowed analysis of the expected shapes and positions of observable robot clusters. We found a high correlation in the challenges posed by both modeling techniques and we highlighted the inherent problems of inferring emergent macroscopic rules from a microscopic description of swarm behavior.}}, author = {{Schmickl, Thomas and Hamann, Heiko and Wörn, Heinz and Crailsheim, Karl}}, issn = {{0921-8890}}, journal = {{Robotics and Autonomous Systems}}, number = {{9}}, pages = {{913--921}}, title = {{{Two different approaches to a macroscopic model of a bio-inspired robotic swarm}}}, doi = {{10.1016/j.robot.2009.06.002}}, volume = {{6}}, year = {{2009}}, } @inproceedings{20259, author = {{Hamann, Heiko and Troch, Inge and Breitenecker, F.}}, booktitle = {{MATHMOD 2009 - 6th Vienna International Conference on Mathematical Modelling}}, title = {{{Pattern Formation as a Transient Phenomenon in the Nonlinear Dynamics of a Multi-Agent System}}}, year = {{2009}}, } @phdthesis{20262, author = {{Hamann, Heiko}}, isbn = {{9783642133763}}, issn = {{1867-4925}}, title = {{{Space-Time Continuous Models of Swarm Robotic Systems}}}, doi = {{10.1007/978-3-642-13377-0}}, year = {{2008}}, } @inproceedings{20367, author = {{Hamann, Heiko and Wörn, Heinz}}, booktitle = {{The tenth International Conference on Simulation of Adaptive Behavior (SAB'08)}}, isbn = {{9783540691334}}, issn = {{0302-9743}}, pages = {{447----456}}, title = {{{Aggregating Robots Compute: An Adaptive Heuristic for the Euclidean Steiner Tree Problem}}}, doi = {{10.1007/978-3-540-69134-1_44}}, volume = {{5040}}, year = {{2008}}, } @inproceedings{20368, abstract = {{We present a comparative study of two spatially resolved macroscopic models of an autonomous robotic swarm. In previous experiments, the collective behavior of 15 autonomous swarm robots, driven by a simple bio-inspired control algorithm, was investigated: in two different environmental conditions, the ability of the robots to aggregate below a light source was tested. Distinct approaches to predict the dynamics of the spatial distribution were made by two different modeling approaches: one model was constructed in a compartmental manner (ODEs). In parallel, a space-continuous model (PDEs) was constructed. Both models show a high degree of similarity concerning the modeling of concrete environmental factors (light), but due to their different basic approaches, show also significant differences in their implementation. However, the predictions of both models compare well to the observed behavior of the robotic swarm, thus both models can be used to develop further extensions of the algorithm as well as different experimental setups without the need to run extensive real robotic preliminary experiments.}}, author = {{Hamann, Heiko and Schmickl, Thomas and Wörn, Heinz and Crailsheim, Karl}}, booktitle = {{IEEE/RSJ 2008 International Conference on Intelligent Robots and Systems (IROS'08)}}, pages = {{1415----1420}}, publisher = {{IEEE Press}}, title = {{{Spatial Macroscopic Models of a Bio-Inspired Robotic Swarm Algorithm}}}, doi = {{10.1109/IROS.2008.4651038}}, year = {{2008}}, } @article{20369, abstract = {{Designing and analyzing self-organizing systems such as robotic swarms is a challenging task even though we have complete knowledge about the robot’s interior. It is difficult to determine the individual robot’s behavior based on the swarm behavior and vice versa due to the high number of agent–agent interactions. A step towards a solution of this problem is the development of appropriate models which accurately predict the swarm behavior based on a specified control algorithm. Such models would reduce the necessary number of time-consuming simulations and experiments during the design process of an algorithm. In this paper we propose a model with focus on an explicit representation of space because the effectiveness of many swarm robotic scenarios depends on spatial inhomogeneity. We use methods of statistical physics to address spatiality. Starting from a description of a single robot we derive an abstract model of swarm motion. The model is then extended to a generic model framework of communicating robots. In two examples we validate models against simulation results. Our experience shows that qualitative correctness is easily achieved, while quantitative correctness is disproportionately more difficult but still possible.}}, author = {{Hamann, Heiko and Wörn, Heinz}}, issn = {{1935-3812}}, journal = {{Swarm Intelligence}}, number = {{2-4}}, pages = {{209--239}}, title = {{{A framework of space–time continuous models for algorithm design in swarm robotics}}}, doi = {{10.1007/s11721-008-0015-3}}, volume = {{2}}, year = {{2008}}, } @inproceedings{20374, author = {{Dorigo, Marco and Hamann, Heiko and Szymanski, Marc and Wörn, Heinz and Shi, Yuhui}}, booktitle = {{IEEE Swarm Intelligence Symposium, Honolulu, USA, April 1-5}}, pages = {{310----315}}, publisher = {{IEEE Press}}, title = {{{Orientation in a Trail Network by Exploiting its Geometry for Swarm Robotics}}}, doi = {{10.1109/SIS.2007.367953}}, year = {{2007}}, } @inproceedings{20431, author = {{Hamann, Heiko and Wörn, Heinz and Sahin, Erol and Spears, Winfield and Winfield, Winfield}}, booktitle = {{Swarm Robotics - Second SAB 2006 International Workshop}}, pages = {{43----55}}, title = {{{An analytical and spatial model of foraging in a swarm of robots}}}, doi = {{10.1007/978-3-540-71541-2_4}}, volume = {{4433}}, year = {{2007}}, } @inproceedings{20432, abstract = {{Designing and implementing artificial self-organizing systems is a challenging task since they typically behave non- intuitive and only little theoretical foundations exist. Predicting a system of many components with a huge amount of interactions is beyond human skills. The currently common use of simulations for design support is not satisfying, as it is time-consuming and the results are most likely sub- optimal. In this work, we present the derivation of an analytical, time-, and space-continuous model for a swarm of autonomous robots based on the Fokker-Planck equation. While the motion model is in most parts physically motivated, the communication model is based on a heuristic approach. A showcase application to a recently proposed scenario of collective perception in a huge swarm of robots with very limited abilities is given and the simulation results are compared to the model. Despite the high level of abstraction, the prediction discrepancies are small and the parameters can be mapped one-to-one from the model to the control algorithm. Finally, we give an outlook on the capabilities of the proposed model, discuss its limitations, and suggest an improvement that could reduce the number of empirically determined parameters.}}, author = {{Hamann, Heiko and Wörn, Heinz}}, booktitle = {{First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007)}}, isbn = {{0769529062}}, pages = {{23----31}}, title = {{{A Space- and Time-Continuous Model of Self-Organizing Robot Swarms for Design Support}}}, doi = {{10.1109/saso.2007.3}}, year = {{2007}}, } @article{20433, author = {{Hamann, Heiko and Wörn, Heinz and Nagy, Marius and Nagy, Naya}}, journal = {{Parallel Processing Letters}}, number = {{3}}, pages = {{287----298}}, title = {{{Embodied Computation}}}, volume = {{17}}, year = {{2007}}, } @inproceedings{20434, abstract = {{Current research in Micro, Nano and Swarm Robots as results of the European projects Miniman, MiCRoN and I-SWARM will be presented. First, the design and the control of 5 to 10cm3 sized mobile micro robots with five degrees of freedom will be shown. They can handle miniaturized parts as for example an optical component or a biological cell with a size in the micrometre-area with an accuracy of 100nm under a microscope or a raster-electron microscope. Second, the design and the control of a 1cm3-sized mobile untethered micro robot will be demonstrated. Here, the robot consists of five parts: the Piezzo locomotion module, the micro control unit, the communication unit, the navigation system and the micro gripper. The mobile robot can be guided and positioned in an arena with an accuracy of 5 micrometre and can be programmed and controlled over the wireless communication unit. Third, the design and the control of 3 × 3 × 3 mm3 sized micro-/nanorobots with 2 degrees of freedom will be presented. The transmission of energy and the communication between the robots is realized via infrared. The robot controller is fully integrated and has limited functionalities. Via basic sensors communication functions and elementary rules and behaviours the micro robot can act in a swarm consisting of hundreds and thousands of robots. Future applications could be monitoring-, inspection-, exploring-tasks etc. of big areas or objects.}}, author = {{Hamann, Heiko and Szymanski, Marc and Wörn, Heinz and Estana, Ramon and Xie, Ming and Dubowsky, Steven}}, booktitle = {{Advances in Climbing and walking robots. Proceedings of 10th International Conference (CLAWAR'07), Singapore, July 16-18}}, pages = {{15----24}}, title = {{{From Micro to Nano and Swarm Robotics}}}, doi = {{10.1142/9789812770189_0003}}, year = {{2007}}, }