publications.bib

 @inproceedings{Haridevan_Kang_Yuan_Shan_2024, address={Chania - Crete, Greece}, title={ROS2-Gazebo Simulator for Drone Applications}, rights={https://doi.org/10.15223/policy-029}, ISBN={9798350357882}, url={https://ieeexplore.ieee.org/document/10556903/}, DOI={10.1109/ICUAS60882.2024.10556903}, abstractNote={This paper introduces ROS2Gazebo Drone, a modular C++ and Python based toolbox based on ROS2 and Gazebo. ROS2GazeboDrone consists of a core module written as a Gazebo System Plugin, that orchestrates the interfaces between Gazebo and Quadrotor. The modular design of toolbox can be used to test perception, path planning, and control algorithms in an efficient manner. The toolbox can be integrated as a ROS2 node as well as a standalone quadrotor simulator. The decoupled and modular architecture enables the extension of this toolbox to any quadrotor model with minimal modifications. We demonstrate the flexibility of our toolbox through demonstrations.}, booktitle={2024 International Conference on Unmanned Aircraft Systems (ICUAS)}, publisher={IEEE}, author={Haridevan, Amal Dev and Kang, Junjie and Yuan, Mingfeng and Shan, Jinjun}, year={2024}, month=jun, pages={1232–1238}, language={en} }
 @inproceedings{Liu_Haridevan_Schofield_Shan_2022, address={Kyoto, Japan}, title={Application of Ghost-DeblurGAN to Fiducial Marker Detection}, rights={https://doi.org/10.15223/policy-029}, ISBN={978-1-66547-927-1}, url={https://ieeexplore.ieee.org/document/9981701/}, DOI={10.1109/IROS47612.2022.9981701}, abstractNote={Feature extraction or localization based on the fiducial marker could fail due to motion blur in real-world robotic applications. To solve this problem, a lightweight generative adversarial network, named Ghost-DeblurGAN, for real-time motion deblurring is developed in this paper. Furthermore, on account that there is no existing deblurring benchmark for such task, a new large-scale dataset, YorkTag, is proposed that provides pairs of sharp/blurred images containing fiducial markers. With the proposed model trained and tested on YorkTag, it is demonstrated that when applied along with fiducial marker systems to motion-blurred images, Ghost-DeblurGAN improves the marker detection significantly. The datasets and codes used in this paper are available at: https://github.com/York-SDCNLab/Ghost-DeblurGAN.}, booktitle={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, publisher={IEEE}, author={Liu, Yibo and Haridevan, Amaldev and Schofield, Hunter and Shan, Jinjun}, year={2022}, month=oct, pages={6827–6832}, language={en} }