Abstract
This paper presents an enforcing multi-hop network connectivity algorithm experimentally validated using a modified version of the Darwinian Particle Swarm Optimization (DPSO), denoted as RDPSO (Robotic DPSO) on groups of simulated robots performing a distributed exploration task. This work aims to overcome limitations of multi-robot systems (MRS) in difficult scenarios (e.g., search and rescue) concerning the need and the ability to actively maintain an available inter-robot communication channel, through the development of effective multi-robot cooperation without relying on a preexisting communication network. Although there is no linear relationship between the number of robots (i.e., nodes) and the maximum communication range, experimental results show that the decreased performance by the developed algorithm under communication constraints can be overcome by slightly increasing the number of robots as the maximum communication range is decreased. © 2011 IEEE.

Abstract
This paper analyzes the dynamic performance of two cooperative robot manipulators. It is studied the implementation of fractional-order algorithms in the position/force control of two cooperating robotic manipulators holding an object. The simulations reveal that fractional algorithms lead to performances superior to classical integer-order controllers. © 2008 IEEE.

Abstract
In most real multi-robot applications, e. g., search-and-rescue, cooperative robots have to fulfill their tasks while driving and communicating among themselves without the aid of a network infrastructure. However, initially deploying autonomously a wireless sensor robot network in a real environment has not taken the proper attention. This paper presents an autonomous and realistic initial deployment strategy, based on a hierarchical approach, in which exploring agents, denoted as scouts, are autonomously deployed through explicit cooperation with supporting agents, denoted as rangers. To evaluate the initial deployment strategy proposed, experimental results with a team of heterogeneous robots are conducted using modified low-cost platforms previously developed by the authors. Preliminary results show the effectiveness of the method and pave the way for a whole series of possible new approaches.

Abstract
This paper presents a collective foraging algorithm designed to simulate natural selection in a group of swarm robots. The Robotic Darwinian Particle Swarm Optimization (RDPSO) previously proposed is improved using fractional calculus theory and evaluated on real low-cost mobile robots performing a distributed foraging task. This work aims at evaluating this novel exploration strategy, by studying the performance of the algorithm within a population of up to 12 robots, under communication constraints. In order to simulate the maximum allowed communication distance, robots were provided with a list of their teammates' addresses. Experimental results show that only 4 robots are needed to accomplish the proposed mission and, independently on the number of robots, maximum communication distance and fractional coefficient, the optimal solution is achieved in approximately 90% of the experiments.

Abstract
This paper presents the development of computational simulation based on the dynamics of a robotic bird. The study analyze the wing angle of attack and the velocity of the bird, the tail influence, the gliding flight and the flapping flight with different strategies and algorithms of control. The results are positive for the construction of flying robots. Some highlights are given about the fist implemented architecture of the structure of a robotic bird. This platform consists on a body, wings and tail with actuators independently controlled though a microcontroller; a radio transmission system and batteries are used in order to avoid wired connections between the computer and the robot.

Abstract
This paper covers a wide knowledge of physical and dynamical models useful for building flying robots and a new generation of flying platform developed in the similarity of flying animals. The goal of this work is to develop a simulation environment and dynamic control using the high-level calculation tool MatLab and the modeling, simulation, and analysis of dynamic systems tool Simulink. Once created the dynamic models to study, this work involves the study and understanding of the dynamic stability criteria to be adopted and their potential use in the control of flying models.