Abstract

Abstract
This paper addresses the problem of decentralized exploration and mapping of unknown environment by a multiple robot team. The exploration methodology relies on individual decision rules and communication of topological maps to achieve efficient and fast mapping, minimizing overlap of explored space. This distributed solution allows scalability of the proposed methods. Each robot broadcasts a graph representing the topological map, with information of exploration status of each region. Therefore, this kind of information can be transmitted to robots that are not in the communication range, through other robots in a multi-hop network. This work has been tested in simulation, and the results demonstrate the performance improvements and robustness that arise from our multirobot approach to exploration.

Abstract
Nowadays, and considering flexibility, industrial robots still present some drawback that prevent them to be used in vast fields of the industry. One of their major limitations is related with their perception skills. In this area, and although the many developments verified on 3D object recognition systems in the research sphere, the number of solutions appearing in the industry level has been slow. Hence, this article tries to clarify some of the motives that difficult the technology transference (in what concerns object recognition) between both worlds. At the same time, it will be presented an industrial case scenario (inserted in an European Project) where some of the problems enumerated during the article are present.

Abstract
In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.

Abstract
In robotics, a reliable simulation tool is an important design and test resource because the performance of algorithms is evaluated before being implemented in real mobile robots. The virtual environment makes it possible to conduct extensive experiments in controlled scenarios, without the dependence of a physical platform, in a faster and inexpensive way. Although, simulators should be able to represent all the relevant characteristics that are present in the real environment, like dynamic (shape, mass, surface friction, etc.), impact simulation, realistic noise, among other factors, in order to guarantee the accuracy and reliability of the results. This paper presents a ROS (Robot Operating System) framework for the SimTwo simulator. ROS is an open-source library that is commonly used for the development of robotic applications since it provides standard services and promotes large-scale integrative robotic research. SimTwo is a realistic simulation software suitable for test and design of several types of robots. This simulator conducts realistic navigation procedures, since the driving systems, the sensors, the mechanical and physical properties of the bodies are precisely modeled. The framework presented in this research provides the integration of ROS-based systems with the SimTwo simulator. Therefore, this framework reduces the risk of damage of expensive robotic platforms and it can be used for the development of new mobile robot controllers, as well as for educational purposes.

Abstract
The problem of homing a mobile robot to a given reference location under unknown relative and absolute positions is addressed in this paper. This problem is easy to solve when all the positions and kinematic variables are known or are observable, but remains a challenge when only range is measured. Its complexity further increases when variable and unknown drifts are added to the motion, which is typical for marine vehicles. Based on the range measurements, it is possible to drive the robot arbitrarily close to the reference. This paper presents a complete solution and demonstrates the validity of the approach based on the Lyapunov theory. The use of models, which are often affected by uncertainties and/or unmodeled terms, is intended to be minimal and only some constraints are imposed on the speed of the robot. We derive a control law that makes the robot converge asymptotically to the reference and prove its stability theoretically. Nevertheless, as it is well known, practical limitations on the actuation can weaken some properties of convergence, namely when the system dynamics require increasing actuation along the approach trajectory. We will demonstrate that the robot reaches a positively invariant set around the reference whose upper bound is determined. Finally, we conclude our work by presenting simulation and experimental data and by demonstrating the validity and the robustness of the method.