CRAS - Indexed Articles in Conferences

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Browsing CRAS - Indexed Articles in Conferences by Author "5446"
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    Comparative Study of Visual Odometry and SLAM Techniques
    ( 2018) Alexandra Nunes ; Matos,A ; Andry Maykol Pinto ; Ana Gaspar ; 5446 ; 6869 ; 6868
    The use of the odometry and SLAM visual methods in autonomous vehicles has been growing. Optical sensors provide valuable information from the scenario that enhance the navigation of autonomous vehicles. Although several visual techniques are already available in the literature, their performance could be significantly affected by the scene captured by the optical sensor. In this context, this paper presents a comparative analysis of three monocular visual odometry methods and three stereo SLAM techniques. The advantages, particularities and performance of each technique are discussed, to provide information that is relevant for the development of new research and novel robotic applications. © Springer International Publishing AG 2018.
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    An Hierarchical Architecture for Docking Autonomous Surface Vehicles
    ( 2019) Aníbal Matos ; Andry Maykol Pinto ; Pedro Nuno ; Renato Jorge Silva ; 7626 ; 5446 ; 5158 ; 7627
    Autonomous Surface Vehicles (ASVs) provide the ideal platform to further explore the many opportunities in the cargo shipping industry, by making it more profitable and safer. This paper presents an architecture for the autonomous docking operation, formed by two stages: a maneuver module and, a situational awareness system to detect a mooring facility where an ASV can safely dock. Information retrieved from a 3D LIDAR, IMU and GPS are combined to extract the geometric features of the floating platform and to estimate the relative positioning and orientation of the moor to the ASV. Then, the maneuver module plans a trajectory to a specific position and guarantees that the ASV will not collide with the mooring facility. The approach presented in this paper was validated in distinct environmental and weather conditions such as tidal waves and wind. The results demonstrate the ability of the proposed architecture for detecting the docking platform and safely conduct the navigation towards it, achieving errors up to 0.107 m in position and 6.58 degrees in orientation.