Abstract
In this paper a vision based groundtruth system for underwater applications is presented. The proposed system as an external validation perception and localization mechanism for underwater trials in the INESC TEC/ISEP underwater robotics test tank. It is comprised by a stereo camera pair with external synchronization and a image processing and data recording host computer. The cameras are disposed in a rigid baseline calibrated using scenario key points. Two target detection algorithms were tested and their results are discussed. One is based on template matching techniques allowing the tracking of arbitrary targets without particular markers and the other on color segmentation with the target vehicle equipped with light markers. Also an example trajectory of a small ROV motion in the task is also presented.

Abstract
In this paper, we propose a cooperative perception framework for multi-robot real-time 3D high dynamic target estimation in outdoor scenarios based on monocular camera available on each robot. The relative position and orientation between robots establishes a flexible and dynamic stereo baseline. Overlap views subject to geometric constraints emerged from the stereo formulation, which allowed us to obtain a decentralized cooperative perception layer. Epipolar constraints related to the global frame are applied both in image feature matching and to feature searching and detection optimization in the image processing of robots with low computational capabilities. In contrast to classic stereo, the proposed framework considers all sources of uncertainty (in localization, attitude and image detection from both robots) in the determination of the objects best 3D localization and its uncertainty. The proposed framework can be later integrated in a decentralized data fusion (DDF) multi-target tracking approach where it can contribute to reduce rumor propagation data association and track initialization issues. We demonstrate the advantages of this approach in real outdoor scenario. This is done by comparing a stereo rigid baseline standalone target tracking with the proposed multi-robot cooperative stereo between a micro aerial vehicle (MAV) and an autonomous ground vehicle (AGV).

Abstract
It is commonly accepted that one of the most important factors for assuring the high performance of an electrical network is the surveillance and the respective preventive maintenance. From a long time ago that TSOs and DSOs incorporate in their maintenance plans the surveillance of the grid, where is included the aerial power lines inspection. Those inspections started by human patrol, including structure climbing when needed and later were substituted by helicopters with powerful sensors and specialised technicians. More recently the Unmanned Aerial Vehicles (UAV) technology has been used, taking advantage of its numerous advantages. This paper addresses the problem of improving the real-time perception capabilities of UAVs for endowing them with capabilities for safe and robust autonomous and semi-autonomous operations. It presents a new vision based power line detection algorithm denoted by PLineD, able to improve the detection robustness even in the presence of image with background noise. The algorithm is tested in real outdoor images of a dataset with multiple backgrounds and weather conditions. The experimental results demonstrate that the proposed approach is effective and able to implemented in real-time image processing pipeline.

Abstract
Field experiments with a team of heterogeneous robots require human and hardware resources which cannot be implemented in a straightforward manner. Therefore, simulation environments are viewed by the robotic community as a powerful tool that can be used as an intermediate step to evaluate and validate the developments prior to their integration in real robots. This paper evaluates a novel multi-robot heterogeneous cooperative perception framework based on monocular measurements under the MORSE robotic simulation environment. The simulations are performed in an outdoor environment using a team of Micro Aerial Vehicles (MAV) and an Unmanned Ground Vehicle (UGV) performing distributed cooperative perception based on monocular measurements. The goal is to estimate the 3D target position.

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
INESC TEC is strongly committed to become a center of excellence in maritime technology and, in particular, deep sea technology. The STRONGMAR project aims at creating solid and productive links in the global field of marine science and technology between INESC TEC and established leading research European institutions, capable of enhancing the scientific and technological capacity of INESC TEC and linked institutions, helping raising its staff's research profile and its recognition as a European maritime research center of excellence. The STRONGMAR project seeks complementarity to the TEC4SEA research infrastructure: on the one hand, TEC4SEA promotes the establishment of a unique infrastructure of research and technological development, and on the other, the STRONGMAR project intends to develop the scientific expertise of the research team of INESC TEC.