Abstract
In this paper we present an autonomous ground robot developed for outdoor applications in unstructured scenarios. The robot was developed as a versatile robotics platform for development, test and validation of research in navigation, control, perception and multiple robot coordination on all terrain scenarios. The hybrid systems approach to the control architecture is discussed in the context of multiple robot coordination. The robot modular hardware and software architecture allows for a wide range of mission applications. A precise navigation system based on high accuracy GPS is used for accurate 3D environment mapping tasks. The vision system is also presented along with some example results from stereo target tracking in operational environment.

Abstract
Robotics research in Portugal is increasing every year, but few students embrace it as one of their first choices for study. Until recently, job offers for engineers were plentiful, and those looking for a degree in science and technology would avoid areas considered to be demanding, like robotics. At the undergraduate level, robotics programs are still competing for a place in the classical engineering graduate curricula. Innovative and dynamic Master's programs may offer the solution to this gap. The Master's degree in autonomous systems at the Instituto Superior de Engenharia do Porto (ISEP), Porto, Portugal, was designed to provide a solid training in robotics and has been showing interesting results, mainly due to differences in course structure and the context in which students are welcomed to study and work.

Abstract
We present a novel approach to 6D visual odometry for vehicles with calibrated stereo cameras. A dense probabilistic egomotion (5D) method is combined with robust stereo feature based approaches and Extended Kalman Filtering (EKF) techniques to provide high quality estimates of vehicle's angular and linear velocities. Experimental results show that the proposed method compares favorably with state-the-art approaches, mainly in the estimation of the angular velocities, where significant improvements are achieved.

Abstract
The robotics community is concerned with the ability to infer and compare the results from researchers in areas such as vision perception and multi-robot cooperative behavior. To accomplish that task, this paper proposes a real-time indoor visual ground truth system capable of providing accuracy with at least more magnitude than the precision of the algorithm to be evaluated. A multi-camera architecture is proposed under the ROS (Robot Operating System) framework to estimate the 3D position of objects and the implementation and results were contextualized to the Robocup Middle Size League scenario.

Abstract
In the context of detection, location and tracking of human targets with combination of thermographic and visible cameras, this paper addresses the problem of geometric calibration of thermographic and visible spectrum cameras necessary for the stereo perception of targets in the robot frame. A method for precise geometric calibration of thermographic and visible cameras in the autonomous surface vehicle (ASV) ROAZ II is presented. The method combine the utilization of special patterns for intrinsic calibration of thermographic cameras, with the usage of a high-resolution 3D laser scanner for the extrinsic calibration, relating the cameras frames with the robot frame. Calibration process results are presented and analyzed.

Abstract
Autonomous mobile robots perception systems are complex multi-sensors systems. Information from different sensors, placed in different parts of the platforms, need to be related and fused into some representation of the world or robot state. For that, the knowledge of the relative pose (position and rotation) between sensors frames and the platform frame plays a critical role. The process to determine those is called extrinsic calibration. This paper addresses the development of automatic robot calibration tool for Middle Size League Robots with rotating directional cameras, such as the ISePorto team robots. The proposed solution consists on a robot navigating in a path, while acquiring visual information provided by a known target positioned in a global reference frame. This information is then combined with wheel odometry sensors, robot rotative axis encoders and gyro information within an Extend Kalman filter framework, that estimates all parameters required for the sensors angles and position determination related to the robot body frame. We evaluated our solution, by performing several trials and obtaining similar results to the previous used manual calibration procedure, but with a much less time consuming performance and also without being susceptible to human error.