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Physicomimetics: Physics-Based Swarm Intelligence by William M. Spears (auth.), William M. Spears, Diana F.

By William M. Spears (auth.), William M. Spears, Diana F. Spears (eds.)

Standard methods to realizing swarms depend on notion from biology and are often lined by means of the time period “biomimetics”. This publication specializes in a unique, complementary thought, particularly physics. The editors have brought the time period 'physicomimetics' to consult physics-based swarm ways, which provide merits. First, they catch the concept that “nature is lazy', that means that physics-based structures continually practice the minimum volume of labor precious, that's an extremely vital virtue in swarm robotics. moment, physics is the main predictive technology, and will decrease complicated structures to easy techniques and equations that codify emergent habit and aid us to layout and comprehend swarms.

The editors consolidated over a decade of labor on swarm intelligence and swarm robotics, organizing the booklet into 19 chapters as follows. half I introduces the idea that of swarms and gives the reader a physics instructional; half II bargains with functions of physicomimetics, so as of elevated complexity; half III examines the requisites of the provided algorithms and demonstrates genuine robotic implementations; half IV demonstrates how the idea can be utilized to layout swarms from first ideas and gives a unique set of rules that handles altering environments; eventually, half V exhibits that physicomimetics can be utilized for functionality optimization, relocating the reader from problems with swarm robotics to swarm intelligence. The textual content is supported with a downloadable package deal containing simulation code and video clips of operating robots.

This booklet is acceptable for proficient highschool and undergraduate scholars, in addition to researchers and graduate scholars within the components of synthetic intelligence and robotics.

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Additional info for Physicomimetics: Physics-Based Swarm Intelligence

Example text

5. When a new particle comes in (middle right), it moves to one of the two intersection points, as shown in the lower right picture. This process continues until all seven particles have been introduced, as shown in Fig. 7. Note the resemblance between this end result and that shown in Fig. 5. avi”. Al- 16 William M. Spears Fig. 7: Gravity well depiction of final triangular lattice with seven particles though the details have not been fully fleshed out, we have shown how a compass construction can be mapped to a physics rubber sheet model.

You will see both phrases in this book, depending on the context. It is the last sentence, however, that I think is the most important. It stresses the notion that physicomimetics is not simply F = ma. It is a way of thinking about problems. As stated earlier, physics provides new metaphors for approaching these problems. 18 William M. Spears Fig. 6 What Is This Book About? In a nutshell, this book provides a well-documented discussion of how a research program starts and grows. This is an unusual perspective, but important, because it provides younger readers the opportunity to see just how science is done.

Based on principles of fluid dynamics, a physicomimetics algorithm called “fluxotaxis” was created. This algorithm uses sensor mesh computations to drive the swarm lattice to a chemical source emitter. Simulations indicate that fluxotaxis is superior to biomimetic approaches. Results are also shown on our first Maxelbot prototype robots, indicating that a small swarm of three robots (with one chemical sensor per robot) outperforms one robot with four sensors. This is an excellent demonstration of an application that is perfect for swarms.

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