ISEP – LSA – Comunicações em eventos científicos
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- Modelação de um Mercado da Pequena Geração Dispersa através de Agentes e Serviços WebPublication . Correia, Nuno Alexandre Sarmento; Malucelli, Andreia; Fidalgo, José Nuno; Custódio, Luís Manuel Marques; Malheiro, BeneditaO objectivo deste trabalho é a criação de um modelo do mercado energético da pequena geração dispersa através de serviços Web, agentes m´oveis e leilões. Neste cenário, o mercado, supervisionado pelo leiloeiro, ´e constituído basicamente por dois tipos de actores: os vendedores – com uma determinada carteira de pequenos produtores de energia, equipados com diversos tipos de geradores, e os compradores – entidades que distribuem e comercializam energia, bem como grandes consumidores. Apresenta-se a arquitectura adoptada, composta por agentes estáticos e agentes m´oveis, assim como a metodologia de desenvolvimento integrado elegida. Esta metodologia especifica uma abordagem, suportada pela tecnologia XML, que permite, a partir da informação relativa aos intervenientes, criar uma ontologia comum de representação do conhecimento do domínio, gerar automaticamente os agentes que modelam os intervenientes e, por ultimo, ´ transformá-los em serviços Web. Os agentes compradores e vendedores participam no mercado através de agentes m´oveis, a quem delegam a sua representação durante o leilão. O trabalho, que está em curso, encontra-se na fase do desenvolvimento dos agentes/serviços Web.
- Autonomous bathymetry for risk assessment with ROAZ robotic surface vehiclePublication . Ferreira, H.; Almeida, C.; Martins, A.; Almeida, J.; Dias, N.; Dias, A.; Silva, E.The use of unmanned marine robotic vehicles in bathymetric surveys is discussed. This paper presents recent results in autonomous bathymetric missions with the ROAZ autonomous surface vehicle. In particular, robotic surface vehicles such as ROAZ provide an efficient tool in risk assessment for shallow water environments and water land interface zones as the near surf zone in marine coast. ROAZ is an ocean capable catamaran for distinct oceanographic missions, and with the goal to fill the gap were other hydrographic surveys vehicles/systems are not compiled to operate, like very shallow water rivers and marine coastline surf zones. Therefore, the use of robotic systems for risk assessment is validated through several missions performed either in river scenario (in a very shallow water conditions) and in marine coastlines.
- Environmental modeling with precision navigation using ROAZ autonomous surface vehiclePublication . Ferreira, Hugo Miguel; Almeida, Carlos; Martins, Alfredo; Almeida, José Miguel; Dias, André; Silva, Guilherme; Silva, EduardoThe use of robotic vehicles for environmental modeling is discussed. This paper presents diverse results in autonomous marine missions with the ROAZ autonomous surface vehicle. The vehicle can perform autonomous missions while gathering marine data with high inertial and positioning precision. The underwater world is an, economical and environmental, asset that need new tools to study and preserve it. ROAZ is used in marine environment missions since it can sense and monitor the surface and underwater scenarios. Is equipped with a diverse set of sensors, cameras and underwater sonars that generate 3D environmental models. It is used for study the marine life and possible underwater wrecks that can pollute or be a danger to marine navigation. The 3D model and integration of multibeam and sidescan sonars represent a challenge in nowadays. Adding that it is important that robots can explore an area and make decisions based on their surroundings and goals. Regard that, autonomous robotic systems can relieve human beings of repetitive and dangerous tasks.
- Visual-Inertial SLAM for Precise 3D Mapping of Underground EnvironmentsPublication . Ferreira, António Bernardo; Almeida, Jose Miguel; Silva, EduardoThe underground scenarios are one of the most challenging environments for accurate and precise 3D mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS outside the tunnel. Results from the localization strategy and the modelling process are presented.
- Towards a Mobile Three-dimensional Modelling System for Underground StructuresPublication . Ferreira, António Bernardo; Almeida, José Miguel; Silva, EduardoThis paper addresses the three-dimensional modelling of large scale underground galleries, such as traffic tunnels and mines. This work employs techniques from mobile robotics to achieve an autonomous mobile modelling system, adapted to general underground environments. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This work aims to extend the modeling capability to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF) and complemented by the introduction of inertial measurements in the prediction step, allows our system to build threedimensional models and localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity, which emerges from the absence of metric measurements in monocular images. The monocular visual features used in MonoSLAM were extracted by the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. To build the model, vertical cross-sections of the gallery, acquired by a laser range finder sensor, are placed on a common reference frame using the estimated localization. The system was tested based on a dataset acquired inside a real road tunnel. Results from the localization strategy and the modelling process are presented.
- Application of Visual-Inertial SLAM for 3D Mapping of Underground EnvironmentsPublication . Ferreira, António Bernardo; Almeida, José Miguel; Silva, EduardoThe underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.
- Vision-Based Assisted Teleoperation for Inspection Tasks with a Small ROVPublication . Costa, Maria J.; Gonçalves, Pedro; Martins, Alfredo; Silva, EduardoIt is well-known that ROVs require human intervention to guarantee the success of their assignment, as well as the equipment safety. However, as its teleoperation is quite complex to perform, there is a need for assisted teleoperation. This study aims to take on this challenge by developing vision-based assisted teleoperation maneuvers, since a standard camera is present in any ROV. The proposed approach is a visual servoing solution, that allows the user to select between several standard image processing methods and is applied to a 3-DOF ROV. The most interesting characteristic of the presented system is the exclusive use of the camera data to improve the teleoperation of an underactuated ROV. It is demonstrated through the comparison and evaluation of standard implementations of different vision methods and the execution of simple maneuvers to acquire experimental results, that the teleoperation of a small ROV can be drastically improved without the need to install additional sensors.
- Ball Sensing in a Leg Like Robotic KickerPublication . Logghe, Jonas; Dias, André; Almeida, José Miguel; Martins, Alfredo; Silva, EduardoThe trend to have more cooperative play and the increase of game dynamics in Robocup MSL League motivates the improvement of skills for ball passing and reception. Currently the majority of the MSL teams uses ball handling devices with rollers to have more precise kicks but limiting the capability to kick a moving ball without stopping it and grabbing it. This paper addresses the problem to receive and kick a fast moving ball without having to grab it with a roller based ball handling device. Here, the main difficulty is the high latency and low rate of the measurements of the ball sensing systems, based in vision or laser scanner sensors.Our robots use a geared leg coupled to a motor that acts simultaneously as the kicking device and low level ball sensor. This paper proposes a new method to improve the capability for ball sensing in the kicker, by combining high rate measurements from the torque and energy in the motor and angular position of the kicker leg. The developed method endows the kicker device with an effective ball detection ability, validated in several game situations like in an interception to a fast pass or when chasing the ball where the relative speed from robot to ball is low. This can be used to optimize the kick instant or by the embedded kicker control system to absorb the ball energy.
- Support System for Rational Use of Electric EnergyPublication . Teixeira, Tiago; Malheiro, BeneditaThis paper presents the system developed to promote the rational use of electric energy among consumers and, thus, increase the energy efficiency. The goal is to provide energy consumers with an application that displays the energy consumption/production profiles, sets up consuming ceilings, defines automatic alerts and alarms, compares anonymously consumers with identical energy usage profiles by region and predicts, in the case of non-residential installations, the expected consumption/production values. The resulting distributed system is organized in two main blocks: front-end and back-end. The front-end includes user interface applications for Android mobile devices and Web browsers. The back-end provides data storage and processing functionalities and is installed in a cloud computing platform - the Google App Engine - which provides a standard Web service interface. This option ensures interoperability, scalability and robustness to the system.
- 6D Visual Odometry with Dense Probabilistic Egomotion EstimationPublication . Silva, Hugo Miguel; Bernardino, Alexandre; Silva, EduardoWe 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.