Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book contains various works presented at the Dynamics Days Latin America and the Caribbean (DDays LAC) 2018. Since its beginnings, a key goal of the DDays LAC has been to promote cross-fertilization of ideas from different areas within nonlinear dynamics. On this occasion, the contributions range from experimental to theoretical research, including (but not limited to) chaos, control theory, synchronization, statistical physics, stochastic processes, complex systems and networks, nonlinear time-series analysis, computational methods, fluid dynamics, nonlinear waves, pattern formation, population dynamics, ecological modeling, neural dynamics, and systems biology. The interested reader will find this book to be a useful reference in identifying ground-breaking problems in Physics, Mathematics, Engineering, and Interdisciplinary Sciences, with innovative models and methods that provide insightful solutions. This book is a must-read for anyone looking for new developments of Applied Mathematics and Physics in connection with complex systems, synchronization, neural dynamics, fluid dynamics, ecological networks, and epidemics.

self-organization --- temporal aliasing effect --- point scatterer --- recurrence time --- calcium signals --- theta neuron --- synchrony --- neural network --- reaction fronts --- cyclic dynamics --- annular billiard --- convection --- local field potential --- complex systems --- Dicke model --- coupled oscillators --- diffusive instabilities --- Slater’s theorem --- stochastic processes --- nonlinear dynamics --- computational methods --- waves --- ecological methods --- sampling rates --- out of equilibrium system --- predator–prey system --- IP3Rs dsitribution --- birthday problem --- mean field models --- population dynamics --- puffs --- delay bifurcation --- epidemic models --- suppression of synchronization --- population biology --- Lyapunov exponent --- Markov processes --- synchronization

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties:

n/a --- self-organization --- signal source localization --- multi-robot system --- sensor deployment --- parallel technique --- shape normalization --- genetic algorithm --- multiple robots --- optimization --- improved potential field --- optimal configuration --- autonomous docking --- asymmetrical interaction --- comparison --- behaviors --- patterns --- self-assembly robots --- congestion control --- surface-water environment --- target recognition --- coordinate motion --- UAV swarms --- formation reconfiguration --- swarm robotics --- swarm intelligence --- artificial bee colony algorithm --- obstacle avoidance --- fish swarm optimization --- search algorithm --- robotics --- time-difference-of-arrival (TDOA) --- formation --- mobile robots --- formation control --- meta-heuristic --- event-triggered communication --- search --- virtual structure --- 3D model identification --- surveillance --- event-driven coverage --- scale-invariant feature transform --- system stability --- Swarm intelligence algorithm --- bionic intelligent algorithm --- unmanned aerial vehicle --- underwater environment --- artificial flora (AF) algorithm --- swarm behavior --- weighted implicit shape representation --- Cramer–Rao low bound (CRLB) --- environmental perception --- particle swarm optimization --- modular robots --- cooperative target hunting --- virtual linkage --- multi-AUV --- consensus control --- panoramic view --- nonlinear disturbance observer --- sliding mode controller --- path optimization --- Swarm Chemistry --- multi-agents --- Cramer-Rao low bound (CRLB)