Abstract

Abstract
The research proposes a novel technological solution for marker-based human motion capture called WirelessSyncroVision (WSV). The WSV is formed by two main modules: the visual node (WSV-V) which is based on a stereoscopic vision system and the marker node (WSV-M) that is constituted by a 6-DOF active marker. The solution synchronizes the acquisition of images in remote muti-cameras with the ON period of the active marker. This increases the robustness of the stereoscopic system to illumination changes, which is extremely relevant for programming industrial robotic-arms using a human demonstrator programming by demonstration (PbD). In addition, the research presents a robust method named Adaptive and Robust Synchronization (ARS), that is designed for temporal alignment of remote devices using a wireless network. The algorithm models the phase difference as a function of time, measuring the parameters that must be known to predict the synchronization instant between the active marker and the remote cameras. Results demonstrate that the ARS creates a balance between the real-time capability and the performance estimation of the phase difference. Therefore, this research proposes an elegant solution to synchronize image acquisition systems in real-time that is easy to implement with low operational costs; however, the major advantage of the WSV is related to its high level of flexibility since it can be extended toward to other devices besides the PbD, for instance, motion capture, motion analysis, and remote sensoring systems.

Abstract
This paper presents the proposal of a Low cost Mobile Robot prototype with On Board Laser Scanner, prototyped to compete at the Robot (R) Factory Mobile Robot competition. The robot is equipped with a hacked Neato XV-11 Laser Scanner, being a very low cost, alternative, when compared with the current available laser scanners. It is presented the description of its sensors and actuators, providing valuable information that can be used to develop better designs of controllers and localization systems. The robot is equipped with the 37Dx52L, which is a low cost 12v motor equipped with encoders and a 29:1 reduction gearbox, being a very popular actuator in the mobile robotics domain. The robot is also equipped with an USB camera applied to acquire image, that will be processed, in order to provide information concerning the part material status.

Abstract
Particle filters (PFs) are computationally intensive sequential Monte Carlo estimation methods with applications in the field of mobile robotics for performing tasks such as tracking, simultaneous localization and mapping (SLAM) and navigation, by dealing with the uncertainties and/or noise generated by the sensors as well as with the intrinsic uncertainties of the environment. However, the application of PFs with an important number of particles has traditionally been difficult to implement in real-time applications due to the huge number of operations they require. This work presents a hardware implementation on FPGA (field programmable gate arrays) of a PF applied to SLAM which aims to accelerate the execution time of the PF algorithm with moderate resource. The presented system is evaluated for different sensors including a low cost Neato XV-11 laser scanner sensor. First the system is validated by post processing data provided by a realistic simulation of a differential robot, equipped with a hacked Neato XV-11 laser scanner, that navigates in the Robot@Factory competition maze. The robot was simulated using SimTwo, which is a realistic simulation software that can support several types of robots. The simulator provides the robot ground truth, odometry and the laser scanner data. Then the proposed solution is further validated on standard laser scanner sensors in complex environments. The results achieved from this study confirmed the possible use of low cost laser scanner for different robotics applications which benefits in several aspects due to its cost and the increased speed provided by the SLAM algorithm running on FPGA.

Abstract
In this paper an analysis of MicroFactory is carried out and its potential for generating a diversified set of didactic experiences is evaluated. MicroFactory is a robotic competition based on a previously existing competition called Robot@Factory. Robot@Factory is a Portuguese robotic competition whose first edition was held in 2011 in Lisbon. The scenario of the competition simulates a factory which has two warehouses, and eight processing machines. The flow of the materials inside the factory starts at the Incoming Warehouse and ends at the Outgoing Warehouse, eventually passing through one or more processing machines. The robots must collect, transport and position the materials along the process, having to self-localize and navigate while avoiding collisions with walls, obstacles and other robots. There is the option of following predefined tracks present on the floor to ease the navigation problem. Robot@Factory poses challenges like dynamic task scheduling, robot cooperation, trajectory planning, robot navigation with obstacle avoidance, robot self-localization and materials identification and manipulation. Related research contributes to improve AGVs (Automated Guided Vehicle systems) technology. Presently this competition is integrated in Festival Nacional de Robotica, a yearly event which attracts lots of public, contributing also to STEM (Science, Technology, Engineering and Mathematics) popularization. MicroFactory was conceived to be low-cost and easily implementable in a small space, be it a classroom or the school robotics club. The ground area of the factory scenario was reduced to approximately one ninth of its original value. The scenario materials were simplified -the floor is now an A0 printed sheet and the warehouses and machines dimensions are so that they can be 3D printed or made out of LEGO (TM) bricks; both machines and parts had active elements with LEDs and now they are passive. Besides the competition scenario it was also conceived a prototype robot for the competition. It's a 3D printed robot, based on an Arduino board and accessible electronic parts. The creation of this competition is part of a wider Open Source project, aiming to develop project-based collaborative didactic experiences involving robotics and low-cost 3D printed educational robots based on generic electronics to support those experiences. Currently efforts are being dedicated to the inclusion of more sensors in the competition robot, namely low-cost distance sensors and a weight sensor at the claws, the inclusion of different kinds of motors, the development of a new version of the robot incorporating a Raspberry Pi board, the development of a very precise robot localization system, and the conception of a diversified set of didactic experiences based on the MicroFactory competition. This article presents an analysis of MicroFactory and of its inherent challenges. Through this analysis it will be possible to identify topics that can be taught and learned while developing robots to participate in the competition, and to collect elements that will be very useful in the planning and implementation of didactic experiences that work those topics.

Abstract
In this paper it is discussed the proposal of a small robot prototype to be applied in the MicroFactory competition, a downsized version of the Robot@Factory competition. The MicroFactory is intended to help junior competitors to make the transition from the Junior Leagues to the senior competition Robot@Factory. The Robot@Factory competition takes place in an emulated factory plant, where Automatic Guided Vehicles (AGVs) must cooperate to perform tasks. To accomplish their goals the AGVS must deal with localization, navigation, scheduling and cooperation problems, that must be solved autonomously.