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Titlebook: Bio-Inspired Self-Organizing Robotic Systems; Yan Meng,Yaochu Jin Book 2011 Springer Berlin Heidelberg 2011 Robotics.Self-organizing robot

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31#
發(fā)表于 2025-3-26 22:38:46 | 只看該作者
https://doi.org/10.1007/978-3-476-03627-8oneybees and from slime mold aggregation. One of these algorithms is inspired by inter-adult food exchange in honeybees (’trophallaxis’) another one from chemical signaling in slime molds. In addition to the control of robot swarms, control paradigms for multi-modular robotic organisms are presented
32#
發(fā)表于 2025-3-27 03:47:32 | 只看該作者
33#
發(fā)表于 2025-3-27 08:42:14 | 只看該作者
Thomas Br?uninger,Joachim Behnkend use light stimuli to effect a steering mechanism. To explore the generation of complex behaviour from such simple component parts we present a particle based model of . which spontaneously generates complex oscillatory patterns from simple local interactions, is distributed in terms of the origin
34#
發(fā)表于 2025-3-27 11:17:05 | 只看該作者
35#
發(fā)表于 2025-3-27 14:13:10 | 只看該作者
How to Engineer Robotic Organisms and Swarms?oneybees and from slime mold aggregation. One of these algorithms is inspired by inter-adult food exchange in honeybees (’trophallaxis’) another one from chemical signaling in slime molds. In addition to the control of robot swarms, control paradigms for multi-modular robotic organisms are presented
36#
發(fā)表于 2025-3-27 20:21:09 | 只看該作者
Morphogenetic Self-Reconfiguration of Modular Robotsrollers are generic and can in principle be applied to other reconfigurable modular robots. The controller in layer 3 is hardware dependent that mainly deals with the physical constraints of module movements. This hierarchical morphogenetic model is applied to each module of the reconfigurable modul
37#
發(fā)表于 2025-3-28 00:34:30 | 只看該作者
38#
發(fā)表于 2025-3-28 03:31:37 | 只看該作者
39#
發(fā)表于 2025-3-28 07:59:32 | 只看該作者
40#
發(fā)表于 2025-3-28 12:30:48 | 只看該作者
,Die Anf?nge des Hammerklaviers in Italien,uman-made systems with the same robustness, scientists have created artificial analogues of pheromone-based stigmergy, but these systems often suffer from scalability and complexity issues due to the problems associated with mimicking the physics of pheromone diffusion.
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