Abstract
This paper propose a real-time vision architecture for mobile robotics, and describes a current implementation that is characterised by: low computational cost, low latency, low power, high modularity, configuration, adaptability and scalability. A pipeline structure further reduces latency and allows a paralleled hardware implementation. A dedicated hardware vision sensor was developed in order to take advantage of the proposed architecture. A new method using run length encoding (RLE) colour transition allows real-time edge determination at low computational cost. The real-time characteristics and hardware partial implementation, coupled with low energy consumption address typical autonomous systems applications.

Abstract
This work presents a hybrid coordinated manoeuvre for docking an autonomous surface vehicle with an autonomous underwater vehicle. The control manoeuvre uses visual information to estimate the AUV relative position and attitude in relation to the ASV and steers the ASV in order to dock with the AUV. The AUV is assumed to be at surface with only a small fraction of its volume visible. The system implemented in the Autonomous Surface vehicle ROAZ, developed by LSA-ISEP to perform missions in river environment, test autonomous AUV docking capabilities and multiple AUV/ASV coordinated missions is presented. Information from a low cost embedded robotics vision system (LSAVision), along with inertial navigation sensors is fused in an extended kalman filter and used to determine AUV relative position and orientation to the surface vehicle The real time vision processing system is described and results are presented in operational scenario.

Abstract
This paper proposes a novel architecture for real-time 3D ball trajectory estimation with a monocular camera in Middle Size League scenario. Our proposed system consists on detecting possible multiple ball candidates in the image, that are filtered in a multi-target data association layer. Validated ball candidates have their 3D trajectory estimated by Maximum Likelihood method (MLM) followed by a recursive refinement obtained with an Extended Kalman Filter (EKF). Our approach was validated in real RoboCup scenario, evaluated recurring to ground truth information obtained by alternative methods allowing overall performance and quality assessment. © 2012 Springer-Verlag Berlin Heidelberg.

Abstract
In this work a forest fire detection solution using small autonomous aerial vehicles is proposed. The FALCOS unmanned aerial vehicle developed for remote-monitoring purposes is described. This is a small size UAV with onboard vision processing and autonomous flight capabilities. A set of custom developed navigation sensors was developed for the vehicle. Fire detection is performed through the use of low cost digital cameras and near-infrared sensors. Test results for navigation and ignition detection in real scenario are presented.

Abstract
System and mission requirements for the use of Autonomous Underwater Vehicles (AUV) were defined. A requirement analysis was done having in mind the definition of search methodologies involving multiple cooperating vehicles. Control and navigation issues were addressed. Various search strategies were proposed and analyzed in terms of control, navigation and overall system requirements.

Abstract
This paper describes a preliminary and innovative approach to integrated cooperative control and navigation of multi robots dynamic formations that encompasses the simultaneous tracking of opponent team players in robotic football games. Unlike traditional approaches that use self-localization to distribute object position estimates, a coordinated approach to cooperative formation navigation is proposed. The control architecture is based in a hierarchic hybrid systems approach, where distributed maneuvers allow simultaneous navigation and coordination. Our main contributions reside in an integrated control and navigation design framework yielding cooperative localization maneuvers and also some specific maneuver results on both formation estimation and global localization of two robots and two landmarks with bearing only measurements. © 2006 IEEE.