Prof. Dr. Miguel Angel Olivares Mendez
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| Faculty or Centre | Interdisciplinary Centre for Security, Reliability and Trust | ||||
| Department | Space Robotics | ||||
| Postal Address |
Campus Kirchberg, Université du Luxembourg 6, rue Richard Coudenhove-Kalergi L-1359 Luxembourg |
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| Campus Office | L 117C | ||||
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| Telephone | (+352) 46 66 44 5478 | ||||
Dr. Olivares Mendez received the Diploma in Computer Science Engineering in 2006 from the University of Malaga (UMA), Spain, and received the M.Sc. degree in Robotics and Automation and PhD degree in Robotics and Automation from the Industrial Engineering Faculty at the Technical University of Madrid (UPM), Spain, in 2009 and 2013, respectively. He got the Best PhD Thesis award of 2013 by the European Society for Fuzzy Logic and Technology (EUSFLAT). In May 2013 he joined the Interdisciplinary Center for Security Reliability and Trust (SnT) at the University of Luxembourg (Uni.Lu), as Associate Researcher in the Automation & Robotics Research Group. In December 2016 he becomes Research Scientist and major responsible of the research activities on mobiles robotics in the Automation & Robotics Research Group at the SnT-University of Luxembourg.
Since 2013, Dr. Olivares Mendez is acting as Associate Editor for Journal of Intelligent & Robotic Systems (JINT). In 2015, he was selected to be Reviewer Editor for the Robotic Control Systems, part of the journal(s) Frontiers in Robotics and AI. He has been a member of the organizing committee of the Brain Inspired Cognitive Systems (BICS) 2010 conference in Madrid, Spain, serving as Local Arrangement Chair. He was the Financial Chair of the IEEE International Conference on Emerging Technologies and Factory Automation 2015 in Luxembourg and participated as member of the program committee in numerous renowned international scientific conferences in robotics and control. The main research interests of Dr. Olivares Mendez are on unmanned aerial systems, computer vision, sensor fusion, vision-based control, soft-computing control techniques and robotics and automation. He has published over 60 book chapters and papers in scientific journals and conferences. Furthermore, he was the project lead or main supervisor of 7 research projects.
Last updated on: Tuesday, 31 January 2017
Here is my updated cv:
Last updated on: 05 Feb 2015
Here is available all the software developed during my research works.
MOFS-ROS
A Robotics Operative System (ROS) package to develop control system approaches based on Fuzzy Logic. This package is based on the C++ library called Miguel Olivares' Fuzzy Software (MOFS), that was used in several works in the past (publications between 2007 and 2013).
please contact me by email: miguel.olivaresmendez@uni.lu
ARUCO_ROS
A ROS package to process images from the virtual environment of V-REP or from a real camera using an Augmented Reality (AR) code detection. This package is based on the C++ library ArUco, developed by R. Muñoz-Salinas.
please contact me by email: miguel.olivaresmendez@uni.lu
V-REP Quadrotor model
The Virtual Robot Experimental Platform (V-REP) is a powerful tool for robotics tests. It has the option to communicate with ROS. Here is the model of a virtual quadrotor modified to be commanded by velocity commands, to send the onboard camera images to ROS and to receive the control commands.
SnT_ardrone_connection
Here is the ROS package used to communicate by WiFi connection with the AR.Drone (parrot), getting the onboard camera image and sending the control commands. This software is based on the tum_ardrone ROS package.
Vision Control System
This is a ROS package to put across the information extracted from the image processing algorithm (done by the ARUCO_ROS package) to the developed control system (done by the MOFS-ROS package), and also to send the control system output to the virtual or real quadrotor. This package also include another program to run to send basic commands to the real AR.Drone, like take off, land, and the emergency stop. This program also allow to select the specific ARUCO marker to be detected and used for the control of the UAV.
please contact me by email: miguel.olivaresmendez@uni.lu
Last updated on: 22 Oct 2015
Title: Soft-Computing Based Visual Control for Unmanned Vehicles
Abstract:
The aim of this Thesis is to exploit the use of Soft Computing to control
unmanned vehicles using vision. This works goes beyond the typical control
systems used in highly controlled environments, by demonstrating the power
of the Fuzzy Logic Controllers (FLCs) to command aerial and ground vehicles
in a sort of different tasks. A huge amount of real tests are presented in which
the implemented Fuzzy controllers manage a visual pan and tilt platform, a
helicopter, a commercial car and two different types of quadcopters. The use of
the Cross-Entropy method to optimize the behavior of these controllers is also
shown.
All the visual servoing controllers presented in this Thesis were implemented
using the self-developed software tool called MOFS (Miguel Olivares’ Fuzzy
Software). Different visual algorithms were used to acquire the information
of the surrounding environment of the vehicles. The CamShift, homography
decomposition, and augmented reality mark detection among others. This visual
information was used as input of the Fuzzy controllers to manage the vehicle to
do different autonomous tasks.
The steering wheel of a commercial car was controlled to implement a
driverless vehicle for inner-city tests. Long distance of more than 6 km was
covered without driver in a close circuit using a vision line following algorithm.
The limited field of view (50 30 cm) of the system was not an impediment to
reach a top speed of 48km/h and guide the vehicle inside low radius curves.
Static and moving objects like cars were tracking from an unmanned
helicopter controlling an on board pan and tilt visual platform. A full control of
altitude, lateral and forward movements was implemented for an auto-landing
task of a helicopter. An implementation of pitch and heading controllers were
used to command a quadrotor for object following task. The heading was also
controlled for See and Avoid task with this type of UAVs.
The Cross-Entropy optimization method is not wide used for control in the
literature. This Thesis presents the way to optimize the gains, membership
function sets’ position and size and the rules’ weight to improve the behavior of
a Fuzzy controller. This optimization process was done using ROS and Matlab
Simulink to obtain better results for See and Avoid tests for UAVs.
This Thesis demonstrates that the Fuzzy Logic Controllers are widely capable
to command free-model systems in high disturbance environments with a
low cost sensor. The noisy effects of illumination changes and the high uncertain
of the visual detection were manage in a gentle way by this Soft Computing
technique to approach different tasks with different aerial and ground vehicles.
Last updated on: 05 May 2014
2023
Project DragLiner: Harnessing plasma Coulomb drag for satellite deorbiting to keep orbits clean; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;
Scientific Conference (2023, April)
Ultra-Light Floating Platform: An Orbital Emulator for Space Applications; ; ; ;
Poster (2023, May 30)
2022
Enabling Elements of Simulations Digital Twins and its Applicability for Information Superiority in Defence Domain; ; ; ; ; ; ; ;
Scientific Conference (2022, September 29)
Enhancing Rover Teleoperation on the Moon With Proprioceptive Sensors and Machine Learning Techniques; ; ;
in IEEE Robotics and Automation Letters (2022)
Thermophysical Change Detection on the Moon with the Lunar Reconnaissance Orbiter Diviner sensor; ; ; ; ; ;
Scientific Conference (2022)
Concept of an Active Debris Removal 2-step capturing system for small satellites in Low Earth Orbit; ; ; ; ; ; ;
Scientific Conference (2022, October 12)
Emulating Active Space Debris Removal Scenarios in Zero-G Lab; ; ; ; ; ; ;
Presentation (2022, June 02)
Nvidia Omniverse for Active Space Debris Removal Missions, an Overview; ; ; ; ; ; ; ;
Scientific Conference (2022, October 13)
Hardware-in-the-loop Proximity Operations in Cislunar Space; ; ; ; ; ;
Scientific Conference (2022, September 20)
Autonomous control for satellite rendezvous in near-Earth orbits; ; ; ;
Scientific Conference (2022, July)
Learning to Grasp on the Moon from 3D Octree Observations with Deep Reinforcement Learning; ; ;
in Proceedings of 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2022, October 23)
Towards Online System Identification: Benchmark of Model Identification Techniques for Variable Dynamics UAV Applications; ;
in Proceedings of 2022 International Conference on Unmanned Aircraft Systems (ICUAS) (2022, July 26)
ET-Class, an Energy Transfer-based Classification of Space Debris Removal Methods and Missions; ; ; ; ;
in Frontiers in Space Technologies (2022)
2021
Towards incremental autonomy framework for on-orbit vision-based grasping; ; ;
in Proceedings of the International Astronautical Congress, IAC-2021 (2021, October 29)
Enhancing Lunar Reconnaissance Orbiter Images via Multi-frame Super Resolution for Future Robotic Space Missions; ; ;
in IEEE Robotics and Automation Letters (2021)
Lunar Surface Images Enhancement for Space Resources Localization and Extraction; ; ;
Poster (2021, April 19)
SORA Methodology for Multi-UAS Airframe Inspections in an Airport; ; ; ;
in Drones (2021), 5(4 141),
Assessment of a textile portable exoskeleton for the upper limbs' flexion; ; ; ;
Scientific Conference (2021)
Solar-Aerodynamic Formation Flight for 5G Experiments; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;
in Proceedings of the 12th European CubeSatSymposium (2021, November 15)
2020
A Real-Time Approach for Chance-Constrained Motion Planning with Dynamic Obstacles; ; ; ; ;
in IEEE Robotics and Automation Letters (2020), 5(2), 3620-3625
BUILDING A PIECE OF THE MOON: CONSTRUCTION OF TWO INDOOR LUNAR ANALOGUE ENVIRONMENTS; ; ; ;
in Proceedings of the 71st International Astronautical Congress 2020 (2020, October 12)
TESTING ENVIRONMENTS FOR LUNAR SURFACE PERCEPTION SYSTEMS; COMBINING INDOOR FACILITIES, VIRTUAL ENVIRONMENTS AND ANALOGUE FIELD TESTS.; ; ; ; ;
Scientific Conference (2020, October 21)
Low-light image enhancement of permanently shadowed lunar regions with physics-based machine learning; ; ; ; ; ; ; ;
in Low-light image enhancement of permanently shadowed lunar regions with physics-based machine learning (2020, December)
Trajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach; ; ;
in Journal of Intelligent and Robotic Systems (2020), 100
2019
Real-Time Human Head Imitation for Humanoid Robots; ; ; ;
in Proceedings of the 2019 3rd International Conference on Artificial Intelligence and Virtual Reality (2019, July)
Vision-Based Aircraft Pose Estimation for UAVs Autonomous Inspection without Fiducial Markers; ; ;
in IECON 2019-45th Annual Conference of the IEEE Industrial Electronics Society (2019, October)
A case study on the impact of masking moving objects on the camera pose regression with CNNs; ; ;
in 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) (2019, November 25)
Faster Visual-Based Localization with Mobile-PoseNet; ; ;
in International Conference on Computer Analysis of Images and Patterns (2019, August 22)
Deep Reinforcement Learning based Continuous Control for Multicopter Systems; ; ;
in International Conference on Control, Decision and Information CoDIT, Paris 23-26 April 2019 (2019, April 26)
A Real-Time 3D Path Planning Solution for Collision-Free Navigation of Multirotor Aerial Robots in Dynamic Environments; ; ; ;
in Journal of Intelligent and Robotic Systems (2019), 93(1-2), 33-53
2018
Model Predictive Control for Aerial Collision Avoidance in Dynamic Environments; ; ; ;
in 26th Mediterranean Conference on Control and Automation (MED), Zadar, Croatia, 19-22 June 2018 (2018, June)
Collision Avoidance Effects on the Mobility of a UAV Swarm Using Chaotic Ant Colony with Model Predictive Control; ; ; ; ; ;
in Journal of Intelligent and Robotic Systems (2018)
Towards trajectory planning from a given path for multirotor aerial robots trajectory tracking; ; ;
in 2018 International Conference on Unmanned Aircraft Systems (ICUAS), Dallas 12-15 June 2018 (2018, June)
2017
Real-time graph-based SLAM in unknown environments using a small UAV; ;
in 2017 International Conference on Unmanned Aircraft Systems (ICUAS); Miami 13-16 June 2017 (2017)
Evasive Maneuvering for UAVs: An MPC Approach; ;
in ROBOT'2017 - Third Iberian Robotics Conference, Sevilla, Spain, 2017 (2017, November 22)
A Perspective of Security for Mobile Service Robots; ; ; ; ; ;
in Iberian Robotics Conference, Seville, Spain, 2017 (2017, November 22)
Implementation and validation of an event-based real-time nonlinear model predictive control framework with ROS interface for single and multi-robot systems; ; ;
in 2017 IEEE Conference on Control Technology and Applications (CCTA) (2017, August 30)
Hierarchical control of aerial manipulation vehicle; ; ; ; ;
in AIP Conference Proceedings (2017), 1798(1), 020069
Model predictive control for cooperative control of space robots; ; ; ;
in Model predictive control for cooperative control of space robots (2017, January)
Real time degradation identification of UAV using machine learning techniques; ; ;
in International Conference on Unmanned Aircraft Systems ICUAS. Miami, USA, 2017 (2017, June 13)
Operational space control of a lightweight robotic arm actuated by shape memory alloy wires: A comparative study; ; ; ;
in Journal of Intelligent Material Systems and Structures (2017)
Analyzing and improving multi-robot missions by using process mining; ; ;
in Autonomous Robots (2017)
Multi-Robot Interfaces and Operator Situational Awareness: Study of the Impact of Immersion and Prediction; ; ; ; ;
in Sensors (2017), 17(8 1720),
Area exploration with a swarm of UAVs combining deterministic Chaotic Ant Colony Mobility with position MPC; ; ; ; ; ;
in 2017 International Conference on Unmanned Aircraft Systems (ICUAS) (2017, July 27)
2016
A tracking error control approach for model predictive position control of a quadrotor with time varying reference; ; ;
in IEEE International Conference on Robotics and Biomimetics ROBIO, Qingdao, China, 2016 (2016, December 06)
A real-time model predictive position control with collision avoidance for commercial low-cost quadrotors; ; ;
in IEEE Multi-Conference on Systems and Control (MSC 2016), Buenos Aires, Argentina, 2016 (2016, September 20)
A Modularization Approach for Nonlinear Model Predictive Control of Distributed Fast Systems; ; ;
in 24th Mediterranean Conference on Control and Automation (MED), Athens, Greece, June 21-24, 2016 (2016, June 22)
Estimating speed profiles from aerial vision - A comparison of regression based sampling techniques; ;
in Proceedings of the IEEE 24th Mediterranean Conference on Control and Automation (2016, June)
Adaptive Control of Robotic arm with Hysteretic Joint; ; ; ;
in 4th International Conference on Control, Mechatronics and Automation (ICCMA'16), Barcelona, Spain 2016 (2016)
Adaptive Control of Hysteretic Robotic arm in Operational Space; ; ; ;
in 5th International Conference on Mechatronics and Control Engineering ICMCE, venice, Italy, 2016 (2016, December 14)
Control of Aerial Manipulation Vehicle in Operational Space; ; ; ;
in 8th International Conference on Electronics, Computers and Artificial Intelligence, Ploiesti, Romania, 30 June-02 July 2016 (2016, July 01)
Model Predictive Control for Spacecraft Rendezvous; ; ; ;
in 4th International Conference on Control, Mechatronics and Automation ICCMA '16, Barcelona, Spain, 2016 (2016)
UAV degradation identification for pilot notification using machine learning techniques; ; ; ;
in Proceedings of 21st IEEE International Conference on Emerging Technologies and Factory Automation ETFA 2016 (2016, September 06)
Vision-Based Steering Control, Speed Assistance and Localization for Inner-CityVehicles; ; ; ; ;
in Sensors (2016), 16(3), 362
Operational Space Control of a Lightweight Robotic Arm Actuated By Shape Memory Alloy (SMA) Wires; ; ;
in ASME 2016 Conferences on Smart Materials, Adaptive Structures and Intelligent Systems, Vermont 28-30 September 2016 (2016, September)
Lightweight robotic arm actuated by Shape Memory Alloy (SMA) Wires; ; ;
in 8th International Conference on Electronics, Computers and Artificial Intelligence, Ploiesti, Romania, 30 June-02 July 2016 (2016, July 01)
2015
Visual odometry based absolute target geo-location from micro aerial vehicle; ; ;
in International Conference on Robotics, Automation, Control and Embedded Systems (RACE), 2015 (2015, February 20)
Context-based Selection and Execution of Robot Perception Graphs; ; ;
in 20th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA'15) (2015, September)
Vision Based Fuzzy Control Approaches for Unmanned Aerial Vehicles;
in 16th World Congress of the International Fuzzy Systems Association (IFSA) 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT) (2015, July)
Towards an Autonomous Vision-Based Unmanned Aerial System against Wildlife Poachers; ; ; ; ; ; ; ;
in Sensors (2015), 15(12), 29861
Vision Based Fuzzy Control Autonomous Landing with UAVs: From V-REP to Real Experiments; ;
in 23nd IEEE Mediterranean Conference of Control and Automation (MED), 2015, Torremolinos 2015, Spain (2015, June)
2014
Online learning-based robust visual tracking for autonomous landing of Unmanned Aerial Vehicles; ; ;
in Unmanned Aircraft Systems (ICUAS), 2014 International Conference on (2014, May)
Robust real-time vision-based aircraft tracking from Unmanned Aerial Vehicles; ; ; ;
in Robotics and Automation (ICRA), 2014 IEEE International Conference on (2014, May)
Monocular Visual-Inertial SLAM-Based Collision Avoidance Strategy for Fail-Safe UAV Using Fuzzy Logic Controllers; ; ;
in Journal of Intelligent and Robotic Systems (2014), 73(1-4), 513-533
Adaptive Control of Aerial Manipulation Vehicle; ; ;
in Porceedings of the 4th IEEE INTERNATIONAL CONFERENCE ON CONTROL SYSTEM, COMPUTING AND ENGINEERING (2014, November)
HMPMR strategy for real-time tracking in aerial images, using direct methods; ; ; ;
in Machine Vision and Applications (2014), 25(5), 1283-1308
The NOAH Project: Giving a Chance to Threatened Species in Africa with UAVs; ; ; ; ;
in Bissyandé, Tegawendé F.; van Stam, Gertjan (Eds.) e-Infrastructure and e-Services for Developing Countries (2014)
Using the Cross-Entropy method for control optimization: A case study of see-and-avoid on unmanned aerial vehicles; ; ; ;
in Control and Automation (MED), 2014 22nd Mediterranean Conference of (2014, June)
V-REP & ROS Testbed for Design, Test, and Tuning of a Quadrotor Vision Based Fuzzy Control System for Autonomous Landing; ;
in Porceedings of The International Micro Air Vehicle Conference and Competition 2014 (2014, August)
Setting up a testbed for UAV vision based control using V-REP amp; ROS: A case study on aerial visual inspection; ;
in Unmanned Aircraft Systems (ICUAS), 2014 International Conference on (2014)
2013
UAS see-and-avoid strategy using a fuzzy logic controller optimized by Cross-Entropy in Scaling Factors and Membership Functions; ; ;
in Unmanned Aircraft Systems (ICUAS), 2013 International Conference on (2013)
Real-time Adaptive Multi-Classifier Multi-Resolution Visual Tracking Framework for Unmanned Aerial Vehicles; ; ;
in Second Workshop on Research, Development and Education on Unmanned Aerial Systems (RED-UAS 2013) (2013)
Modeling and Control of Aerial Manipulation Vehicle with Visual sensor; ;
in Second Workshop on Research, Development and Education on Unmanned Aerial Systems (RED-UAS 2013) (2013, November)
A Hierarchical Tracking Strategy for Vision-Based Applications On-Board UAVs; ; ; ;
in Journal of Intelligent & Robotic Systems (2013), 72(3-4), 517-539
MAVwork: A Framework for Unified Interfacing between Micro Aerial Vehicles and Visual Controllers; ; ; ;
in Lee, Sukhan; Yoon, Kwang-Joon; Lee, Jangmyung (Eds.) Frontiers of Intelligent Autonomous Systems (2013)
Autonomous Guided Car Using a Fuzzy Controller; ; ; ; ;
in Sen Gupta, Gourab; Bailey, Donald; Demidenko, Serge; Carnegie, Dale (Eds.) Recent Advances in Robotics and Automation (2013)
Cross-Entropy Optimization for Scaling Factors of a Fuzzy Controller: A See-and-Avoid Approach for Unmanned Aerial Systems; ; ;
in Journal of Intelligent and Robotic Systems (2013), 69(1-4), 189-205
Autonomous Landing of an Unmanned Aerial Vehicle using Image-Based Fuzzy Control; ;
in Second Workshop on Research, Development and Education on Unmanned Aerial Systems (RED-UAS 2013) (2013)
2012
A Hierarchical Strategy for Real-Time Tracking On-Board UAVs; ; ; ;
in ICUAS 2012 : 2012 International Conference on Unmanned Aircraft Systems (2012, June)
A hierarchical strategy for real-time tracking on-board uavs; ; ; ;
in ICUAS 2012: 2012 International Conference on Unmanned Aircraft Systems (2012)
Rapid Prototyping Framework for Visual Control of Autonomous Micro Aerial Vehicles; ; ;
in Advances in Intelligent Systems and Computing (2012), 193
See-and-Avoid Quadcopter using Fuzzy Control Optimized by Cross-Entropy; ; ;
in See-and-Avoid Quadcopter using Fuzzy Control Optimized by Cross-Entropy (2012)
Quadcopter see and avoid using a fuzzy controller; ; ;
in Uncertainty modeling in knowlege engineering and decision making : proceedings of the 10th International FLINS Conference (2012)
UAS See-and-Avoid using two different approaches of Fuzzy Control; ; ; ;
in 2012 International Conference on Unmanned Aircraft Systems (ICUAS'12) (2012)
Adaptive Control System based on Lineal Control Theory for the Path-Following Problem of a Car-Like Mobile Robot; ; ; ;
in IFAC Conference on Advances in PID Control PID'12 (2012)
2011
On-board and Ground Visual Pose Estimation Techniques for UAV Control; ; ;
in Journal of Intelligent and Robotic Systems (2011), 61(1-4), 301-320
3D object following based on visual information for Unmanned Aerial Vehicles; ; ;
in Robotics Symposium, 2011 IEEE IX Latin American and IEEE Colombian Conference on Automatic Control and Industry Applications (LARC) (2011)
A visual AGV-urban car using Fuzzy control; ; ; ;
in Automation, Robotics and Applications (ICARA), 2011 5th International Conference on (2011)
Aerial object following using visual fuzzy servoing; ; ; ;
in First Workshop on Research, Development and Education on Unmanned Aerial Systems (RED-UAS 2011) (2011)
2010
A Robotic Eye Controller Based on Cooperative Neural Agents; ; ;
in Proccedings of World Congress on Computational Intelligence (WCCI 2010) (2010)
An intelligent control strategy based on ANFIS techniques in order to improve the performance of a low-cost unmanned aerial vehicle vision system; ; ; ;
in Mechatronics and Embedded Systems and Applications (MESA), 2010 IEEE/ASME International Conference on (2010)
Omnidirectional vision applied to Unmanned Aerial Vehicles (UAVs) attitude and heading estimation; ; ;
in Robotics and Autonomous Systems (2010), 58(6), 809-819
3D pose estimation based on planar object tracking for UAVs control; ; ;
in Proccedings of IEEE International Conference on Robotics and Automation (ICRA) (2010)
Unmanned aerial vehicles UAVs attitude, height, motion estimation and control using visual systems; ; ; ;
in AUTONOMOUS ROBOTS (2010), 29(1), 17-34
Fuzzy Controller for UAV-Landing Task Using 3D-Position Visual Estimation; ; ;
in Proccedings of World Congress on Computational Intelligence (WCCI 2010) (2010)
NON-SYMMETRIC MEMBERSHIP FUNCTION FOR FUZZY-BASED VISUAL SERVOING ONBOARD A UAV; ; ;
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)
Fuzzy-4D/RCS for Unmanned Aerial Vehicles; ; ;
in BICS 2010 Conference on Brain-Inspired Cognitive Systems (2010, July)
2009
Visual 3-D SLAM from UAVs; ; ; ; ; ;
in Journal of Intelligent and Robotic Systems (2009), 55(4-5), 299-321
Computer Vision Onboard UAVs for Civilian Tasks; ; ; ; ; ;
in Journal of Intelligent and Robotic Systems (2009), 54(1-3), 105-135
Trinocular Ground System to Control UAVs; ; ;
in 2009 IEEE-RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (2009)
A Pan-Tilt Camera Fuzzy Vision Controller on an Unmanned Aerial Vehicle; ; ;
in 2009 IEEE-RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (2009)
Visual servoing using fuzzy controllers on an unmanned aerial vehicle; ; ;
in EUROFUSE 2009. workshop on on preference modelling and decision analysis (2009, September)
2008
Vision for guidance and control of UAVs in civilian tasks; ; ; ;
in UAV'08 International Symposium On Unmanned Aerial Vehicles (2008, June)
Fuzzy control system navigation using priority areas; ; ; ;
in Ruan, D (Ed.) COMPUTATIONAL INTELLIGENCE IN DECISION AND CONTROL (2008)
2007
Fuzzy Logic User Adaptive Navigation Control System For Mobile Robots In Unknown Environments;
in Intelligent Signal Processing, 2007. WISP 2007. IEEE International Symposium on (2007, October)
