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See detailVPS-SLAM: Visual Planar Semantic SLAM for Aerial Robotic Systems
Bavle, Hriday UL; Puente, P. De La; How, J. P. et al

in IEEE Access (2020), 8

Indoor environments have abundant presence of high-level semantic information which can provide a better understanding of the environment for robots to improve the uncertainty in their pose estimate ... [more ▼]

Indoor environments have abundant presence of high-level semantic information which can provide a better understanding of the environment for robots to improve the uncertainty in their pose estimate. Although semantic information has proved to be useful, there are several challenges faced by the research community to accurately perceive, extract and utilize such semantic information from the environment. In order to address these challenges, in this paper we present a lightweight and real-time visual semantic SLAM framework running on board aerial robotic platforms. This novel method combines low-level visual/visual-inertial odometry (VO/VIO) along with geometrical information corresponding to planar surfaces extracted from detected semantic objects. Extracting the planar surfaces from selected semantic objects provides enhanced robustness and makes it possible to precisely improve the metric estimates rapidly, simultaneously generalizing to several object instances irrespective of their shape and size. Our graph-based approach can integrate several state of the art VO/VIO algorithms along with the state of the art object detectors in order to estimate the complete 6DoF pose of the robot while simultaneously creating a sparse semantic map of the environment. No prior knowledge of the objects is required, which is a significant advantage over other works. We test our approach on a standard RGB-D dataset comparing its performance with the state of the art SLAM algorithms. We also perform several challenging indoor experiments validating our approach in presence of distinct environmental conditions and furthermore test it on board an aerial robot. Video:https://vimeo.com/368217703Released Code:https://bitbucket.org/hridaybavle/semantic_slam.git. [less ▲]

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See detailRobust real-time vision-based aircraft tracking from Unmanned Aerial Vehicles
Fu, Changhong; Carrio, A.; Olivares Mendez, Miguel Angel UL et al

in Robotics and Automation (ICRA), 2014 IEEE International Conference on (2014, May)

Aircraft tracking plays a key and important role in the Sense-and-Avoid system of Unmanned Aerial Vehicles (UAVs). This paper presents a novel robust visual tracking algorithm for UAVs in the midair to ... [more ▼]

Aircraft tracking plays a key and important role in the Sense-and-Avoid system of Unmanned Aerial Vehicles (UAVs). This paper presents a novel robust visual tracking algorithm for UAVs in the midair to track an arbitrary aircraft at real-time frame rates, together with a unique evaluation system. This visual algorithm mainly consists of adaptive discriminative visual tracking method, Multiple-Instance (MI) learning approach, Multiple-Classifier (MC) voting mechanism and Multiple-Resolution (MR) representation strategy, that is called Adaptive M 3 tracker, i.e. AM 3 . In this tracker, the importance of test sample has been integrated to improve the tracking stability, accuracy and real-time performances. The experimental results show that this algorithm is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant sur- rounding illumination, partial aircraft occlusion, blur motion, rapid pose variation and onboard mechanical vibration, low computation capacity and delayed information communication between UAVs and Ground Station (GS). To our best knowledge, this is the first work to present this tracker for solving online learning and tracking freewill aircraft/intruder in the UAVs. [less ▲]

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See detailOnline learning-based robust visual tracking for autonomous landing of Unmanned Aerial Vehicles
Fu, Changhong; Carrio, A.; Olivares Mendez, Miguel Angel UL et al

in Unmanned Aircraft Systems (ICUAS), 2014 International Conference on (2014, May)

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual ... [more ▼]

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop. [less ▲]

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See detailUAS see-and-avoid strategy using a fuzzy logic controller optimized by Cross-Entropy in Scaling Factors and Membership Functions
Fu, Changhong; Olivares Mendez, Miguel Angel UL; Campoy, P. et al

in Unmanned Aircraft Systems (ICUAS), 2013 International Conference on (2013)

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand-avoid problem using its accurate ... [more ▼]

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand-avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization. [less ▲]

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See detailA visual AGV-urban car using Fuzzy control
Olivares Mendez, Miguel Angel UL; Mellado, I.; Campoy, P. et al

in Automation, Robotics and Applications (ICARA), 2011 5th International Conference on (2011)

The goal of the work described in this paper is to develop a visual line guided system for being used on-board an Autonomous Guided Vehicle (AGV) commercial car, controlling the steering and using just ... [more ▼]

The goal of the work described in this paper is to develop a visual line guided system for being used on-board an Autonomous Guided Vehicle (AGV) commercial car, controlling the steering and using just the visual information of a line painted below the car. In order to implement the control of the vehicle, a Fuzzy Logic controller has been implemented, that has to be robust against curvature changes and velocity changes. The only input information for the controller is the visual distance from the image center captured by a camera pointing downwards to the guiding line on the road, at a commercial frequency of 30Hz. The good performance of the controller has successfully been demonstrated in a real environment at urban velocities. The presented results demonstrate the capability of the Fuzzy controller to follow a circuit in urban environments without previous information about the path or any other information from additional sensors. [less ▲]

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See detail3D object following based on visual information for Unmanned Aerial Vehicles
Mondragón, I. F.; Campoy, P.; Olivares Mendez, Miguel Angel UL et al

in Robotics Symposium, 2011 IEEE IX Latin American and IEEE Colombian Conference on Automatic Control and Industry Applications (LARC) (2011)

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See detailNON-SYMMETRIC MEMBERSHIP FUNCTION FOR FUZZY-BASED VISUAL SERVOING ONBOARD A UAV
Olivares Mendez, Miguel Angel UL; Campoy, P.; Martinez, C. et al

in Ruan, D Li, TR Xu, Y Chen, GQ Kerre, EE (Ed.) COMPUTATIONAL INTELLIGENCE: FOUNDATIONS AND APPLICATIONS: PROCEEDINGS OF THE 9TH INTERNATIONAL FLINS CONFERENCE (2010, August)

This paper presents the definition of non-symmetric membership function for Fuzzy controllers applied to a pan & tilt vision platform onboard an Unmanned Aerial Vehicle. This improvement allows the ... [more ▼]

This paper presents the definition of non-symmetric membership function for Fuzzy controllers applied to a pan & tilt vision platform onboard an Unmanned Aerial Vehicle. This improvement allows the controllers to have a more adaptive behavior to the non-linearities presented in an UAV. This implementation allows the UAV to follow objects in the environment by using Lucas-Kanade visual tracker, in spite of the aircraft vibrations, the movements of the objects and the aircraft, update has been tested in real flights with an unmanned helicopter of the Computer Vision Group at the UPM, with very successful results, attaining a considerable reduction of the error during the tracking tests. [less ▲]

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See detailAn intelligent control strategy based on ANFIS techniques in order to improve the performance of a low-cost unmanned aerial vehicle vision system
Marichal, G. N.; Hernández, A.; Olivares Mendez, Miguel Angel UL et al

in Mechatronics and Embedded Systems and Applications (MESA), 2010 IEEE/ASME International Conference on (2010)

n this paper, an intelligent control approach based on Neuro-Fuzzy systems is presented. A model of a lowcost vision platform for an unmanned aerial system is taken in the study. A simulation platform ... [more ▼]

n this paper, an intelligent control approach based on Neuro-Fuzzy systems is presented. A model of a lowcost vision platform for an unmanned aerial system is taken in the study. A simulation platform including this low-cost vision system and the influence of the helicopter vibrations over this system is shown. The intelligent control approach has been inserted in this simulation platform. Several trials taking these Neuro-Fuzzy systems as a fundamental part of the control strategy have been carried out. Satisfactory results have been achieved in comparison with the results provided by classical techniques. [less ▲]

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See detailFuzzy control system navigation using priority areas
Olivares Mendez, Miguel Angel UL; Campoy, P.; Martinez Luna, Carol UL et al

in Ruan, D (Ed.) COMPUTATIONAL INTELLIGENCE IN DECISION AND CONTROL (2008)

This paper presents an improvement for the software implementation (MOFS) of a user adaptive fuzzy control system for autonomous navigation of mobile robots in unknown environments. This improvement ... [more ▼]

This paper presents an improvement for the software implementation (MOFS) of a user adaptive fuzzy control system for autonomous navigation of mobile robots in unknown environments. This improvement consists of a priority areas definition where the environment is measured by a PLS laser sensor, in order to get a reduction in the number of fuzzy rules and also in the computational cost, and hence obtaining improvements in the trajectory. This system has been tested in a pioneer mobile robot and on a robotic wheelchair, odometry sensors are used to localize the robots and the goal positions. The system is able to drive the robots to their goal position avoiding static and dynamic obstacles, without using any pre-built map. This approach improves the way to measure the danger of the obstacles, the way to follow the walls of corridors and the detection of doors. These improvements reduce the zigzag effect of the previous system by making the trajectories significantly straighter and hence reducing the time to reach the goal position. [less ▲]

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