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Learning a Controller Fusion Network by Online Trajectory Filtering for Vision-based UAV Racing [article]

Matthias Müller, Guohao Li, Vincent Casser, Neil Smith, Dominik L. Michels, Bernard Ghanem
2019 arXiv   pre-print
The network learns a robust controller with online trajectory filtering, which suppresses noisy trajectories and imperfections of individual controllers.  ...  The result is a network that is able to learn a good fusion of filtered trajectories from different controllers leading to significant improvements in overall performance.  ...  Acknowledgments This work was supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research.  ... 
arXiv:1904.08801v1 fatcat:ikybmj57j5grrlswxxp3h3p5ia

Learning a Controller Fusion Network by Online Trajectory Filtering for Vision-Based UAV Racing

Matthias Muller, Guohao Li, Vincent Casser, Neil Smith, Dominik L. Michels, Bernard Ghanem
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
The network learns a robust controller with online trajectory filtering, which suppresses noisy trajectories and imperfections of individual controllers.  ...  The result is a network that is able to learn a good fusion of filtered trajectories from different controllers leading to significant improvements in overall performance.  ...  Acknowledgments This work was supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research.  ... 
doi:10.1109/cvprw.2019.00083 dblp:conf/cvpr/MullerLCSMG19 fatcat:n7w3v7y5qbfqbfrly4z7etnjsa

Table of Contents

2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
of Objects by UAVs 563 Hasan Saribas (missing), Bedirhan Uzun (missing), Burak Benligiray (missing), Onur Eker (missing), and Hakan Cevikalp (missing) Learning a Controller Fusion Network by Online Trajectory  ...  Filtering for Vision-Based UAV Racing 573 Matthias Müller (missing), Guohao Li (missing), Vincent Casser (missing), Neil Smith (missing), Dominik L.  ...  Learning Raw Image Denoising With Bayer Pattern Unification and Bayer Preserving Augmentation 2070 Jiaming Liu (missing) , Chi-Hao Wu (missing) , Yuzhi Wang (missing) , Qin Xu (missing), Yuqian Zhou  ... 
doi:10.1109/cvprw.2019.00004 fatcat:h7xpqwyrofdxniqtxbodn66mpy

A simple vision-based navigation and control strategy for autonomous drone racing [article]

Artur Cyba and Hubert Szolc and Tomasz Kryjak
2021 arXiv   pre-print
Based on the API provided by the manufacturer, we have created a Python application that enables the communication with the drone over WiFi, realises drone positioning based on visual feedback, and generates  ...  In this paper, we present a control system that allows a drone to fly autonomously through a series of gates marked with ArUco tags. A simple and low-cost DJI Tello EDU quad-rotor platform was used.  ...  ArUco markers), use more advanced control strategies and methods (data fusion, trajectory optimisation, approaches based on reinforcement learning), consider reconfigurable devices (FPGA, Zynq SoC) as  ... 
arXiv:2104.09815v1 fatcat:jdrjpryofjgtdeqculkyancg2q

2019 Index IEEE Robotics and Automation Letters Vol. 4

2019 IEEE Robotics and Automation Letters  
., +, LRA April 2019 830-837 Vision-Based Online Learning Kinematic Control for Soft Robots Using Local Gaussian Process Regression.  ...  ., +, LRA July 2019 2691-2698 Vision-Based Online Learning Kinematic Control for Soft Robots Using Local Gaussian Process Regression.  ...  Permanent magnets Adaptive Dynamic Control for Magnetically Actuated Medical Robots.  ... 
doi:10.1109/lra.2019.2955867 fatcat:ckastwefh5chhamsravandtnx4

2020 Index IEEE Robotics and Automation Letters Vol. 5

2020 IEEE Robotics and Automation Letters  
., +, LRA April 2020 2427-2434 Knowledge Transfer Between Different UAVs for Trajectory Tracking. Gaussian Process Online Learning With a Sparse Data Stream.  ...  ., +, LRA April 2020 1891-1898 Synthesis of a Time-Varying Communication Network by Robot Teams With Gated Recurrent Fusion to Learn Driving Behavior from Temporal Multimodal Data.  ... 
doi:10.1109/lra.2020.3032821 fatcat:qrnouccm7jb47ipq6w3erf3cja

Image Generation for Efficient Neural Network Training in Autonomous Drone Racing [article]

Theo Morales, Andriy Sarabakha, Erdal Kayacan
2020 arXiv   pre-print
In autonomous drone racing, one must accomplish this task by flying fully autonomously in an unknown environment by relying only on computer vision methods for detecting the target gates.  ...  Convolutional neural networks offer impressive advances in computer vision but require an immense amount of data to learn.  ...  The latter is fed into the extended Kalman filter (EKF) running on the Intel Aero Flight Controller with a Dronecode PX4 autopilot to obtain more accurate velocity information through sensor fusion with  ... 
arXiv:2008.02596v1 fatcat:nqpulbvu5fhvfdzjqxdszu3er4

2020 Index IEEE Transactions on Vehicular Technology Vol. 69

2020 IEEE Transactions on Vehicular Technology  
Joint Design of Platoon Communication and Control Based on LTE-V2V; 15893-15907 Hong, C.S., see Nguyen, M.N.H., TVT May 2020 5618-5633 Hong, C.S., see Chen, D., TVT May 2020 5634-5646 Hong, C.S.,  ...  see Le, T.H.T., TVT Dec. 2020 15162-15176 Hong, D., Lee, S., Cho, Y.H., Baek, D., Kim, J., and Chang, N Guo, H., Liu, J., and Zhang, Y., Toward Swarm Coordination: Topol-ogy-Aware Inter-UAV Routing  ...  Bera, A., +, TVT June 2020 6680-6687 Rendezvous: Opportunistic Data Delivery to Mobile Users by UAVs Through Target Trajectory Prediction.  ... 
doi:10.1109/tvt.2021.3055470 fatcat:536l4pgnufhixneoa3a3dibdma

From ERL to MBZIRC: Development of An Aerial-Ground Robotic Team for Search and Rescue [chapter]

Barbara Arbanas, Frano Petric, Ana Batinović, Marsela Polić, Ivo Vatavuk, Lovro Marković, Marko Car, Ivan Hrabar, Antun Ivanović, Stjepan Bogdan
2021 Search and Rescue Robotics [Working Title]  
Throughout the chapter, we highlight the evolution of the robotic system based on the experience gained in the ERL competition.  ...  We focus on the implementation of hardware and software modules that enable the deployment of aerial-ground robotic teams in unstructured environments for joint missions.  ...  for control and trajectory execution of UAVs in obstacle-rich environments.  ... 
doi:10.5772/intechopen.99210 fatcat:kbq5opjy2jhepiauunjmqxqgja

Table of Contents

2020 IEEE Robotics and Automation Letters  
Barfoot 1429 A Probabilistic Model-Based Online Learning Optimal Control Algorithm for Soft Pneumatic Actuators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Degani 2403 Musculoskeletal AutoEncoder: A Unified Online Acquisition Method of Intersensory Networks for State Estimation, Control, and Simulation of Musculoskeletal Humanoids . . . . . . . . . . .  ... 
doi:10.1109/lra.2020.2987582 fatcat:3qafzip5xrg5jliyngq4xxvjha

Autonomous Aerial Delivery Vehicles, a Survey of Techniques on how Aerial Package Delivery is Achieved [article]

Jack Saunders, Sajad Saeedi, Wenbin Li
2022 arXiv   pre-print
Furthermore, improved control schemes and vehicle dynamics are better able to model the payload and improved perception algorithms to detect key features within the unmanned aerial vehicle's (UAV) environment  ...  This has been enabled by technological advancements in aerial manipulators and novel grippers with enhanced force to weight ratios.  ...  The second category is online SLAM, which estimates the current pose of the vehicle based on the last sensor data typically using filter based approaches.  ... 
arXiv:2110.02429v2 fatcat:pi2di7z63zfhvolyeuxvdjfb3u

Graph-Based Horizon Line Detection for UAV Navigation

Yong Xu, Hongtao Yan, Yue Ma, Pengyu Guo
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
We then determine the sky-component by cascade filtering and extract the horizon line based on the boundaries of the sky-component.  ...  To address these problems, we propose a graph-based horizon line detection technique that is composed of graph-based image segmentation, connected domain cascade filtering, horizon line extraction, and  ...  of 4 UAVs for the Simulation Docking Race and in a formation of 7 UAVs for the Speed Crossing Race.  ... 
doi:10.1109/jstars.2021.3126586 fatcat:v5pnp5fyurdi5obkxokpxz6sgm

Protect Your Sky: A Survey of Counter Unmanned Aerial Vehicle Systems

Honggu Kang, Jingon Joung, Jinyoung Kim, Joonhyuk Kang, Yong Soo Cho
2020 IEEE Access  
The last part is devoted to a survey of the CUS market with relevant challenges and future visions.  ...  The CUS, also known as a counterdrone system, protects personal, commercial, public, and military facilities and areas from uncontrollable and belligerent UAVs by neutralizing or destroying them.  ...  ACKNOWLEDGMENT The authors wish to express their deep appreciation for the support rendered by the members of the Next-Generation Unmanned Vehicle Wireless Communication Laboratory (including the Mobile  ... 
doi:10.1109/access.2020.3023473 fatcat:boi4ct6lgvdndp4nhkm2hdthwe

Application Specific Drone Simulators: Recent Advances and Challenges

Aakif Mairaj, Asif I. Baba, Ahmad Y. Javaid
2019 Simulation modelling practice and theory  
Security and viability concerns in drone-based applications are growing at an alarming rate. Besides, UAV networks (UAVNets) are distinctive from other ad-hoc networks.  ...  This is achievable by creating a simulator that includes these aspects.  ...  AirSim AirSim is an O/S drone simulator designed by Microsoft's Aerial Informatics and Robotics (AIR), primarily, to introduce it as a useful tool for AI research focusing on deep learning, computer vision  ... 
doi:10.1016/j.simpat.2019.01.004 fatcat:oy4rssrl5fagtixx5wrr747apm

Decentralized Communication-Aware Motion Planning in Mobile Networks: An Information-Gain Approach

Yasamin Mostofi
2009 Journal of Intelligent and Robotic Systems  
More specifically, we show how each node can predict the information gained through its communications, by online learning of link quality measures such as received Signal to Noise Ratio (SNR) and correlation  ...  We finally show that highly correlated deep fades, on the other hand, can degrade the performance drastically for a long period of time.  ...  We then propose a probabilistic decision-making and control framework that integrates both communication and sensing objectives based on online learning of link qualities.  ... 
doi:10.1007/s10846-009-9335-9 fatcat:fb626fpclvd2fm6bi6zhfe5n3q
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