Self-Organized Embedded Sensor/Actuator Networks for ''Smart'' Turbines
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Robots are steadily becoming one of the significant 21st century learning technologies that aim to improve education within both formal and informal environments. Such robots, called Robots for Learning, have so far been utilized as constructionist tools o ...
The collective dynamic behavior of large groups of interacting autonomous agents (swarms) have inspired much research in both fundamental and engineering sciences. It is now widely acknowledged that the intrinsic nonlinearities due to mutual interactions c ...
Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...
Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics ...
Robotic animals are nowadays developed for various types of research, such as bio-inspired robotics, biomimetics and animal behavior studies. The miniaturization of technologies and the increase in performance of embedded systems allowed engineers to devel ...
The ability to efficiently and precisely manipulate objects in inaccessible environments is becoming an essential requirement for many applications of mobile robots, particularly at small sizes. Here, we propose and implement a mobile micromanipulation sol ...
This book is open access under a CC BY 4.0 license. This book bridges the gap between playing with robots in school and studying robotics at the upper undergraduate and graduate levels to prepare for careers in industry and research. Robotic algorithms are ...
Classical models of aerial swarms often describe global coordinated motion as the combination of local interactions that happen at the individual level. Mathematically, these interactions are represented with potential fields. Despite their explanatory suc ...
In this paper we study the automatic synthesis of robotic controllers for the coordinated movement of multiple mobile robots. The algorithm used to learn the controllers is a noise-resistant version of Particle Swarm Optimization, which is applied in two d ...
2014
In current robotics research there is a vast body of work on algorithms and control methods for groups of decentralized cooperating robots, called a swarm or collective. These algorithms are generally meant to control collectives of hundreds or even thousa ...