Vision-based autonomous landing for micro aerial vehicles on targets moving in 3D space
| dc.creator | Robson Olegário de Santana | |
| dc.creator | Leonardo Amaral Mozelli | |
| dc.creator | Armando Alves Neto | |
| dc.date.accessioned | 2025-05-05T15:59:07Z | |
| dc.date.accessioned | 2025-09-08T23:30:23Z | |
| dc.date.available | 2025-05-05T15:59:07Z | |
| dc.date.issued | 2019 | |
| dc.identifier.doi | 10.1109/ICAR46387.2019.8981643 | |
| dc.identifier.uri | https://hdl.handle.net/1843/82019 | |
| dc.language | eng | |
| dc.publisher | Universidade Federal de Minas Gerais | |
| dc.relation.ispartof | 19th International Conference on Advanced Robotics (ICAR) | |
| dc.rights | Acesso Restrito | |
| dc.subject | Robôs - Sistemas de controle | |
| dc.subject | Robótica | |
| dc.subject.other | Aerial robotics | |
| dc.subject.other | 3D Space , Aerial Vehicles , Micro Air Vehicles , Autonomous Landing , Visual Information , Visual Feedback , Monocular , Vision Algorithms , Trajectory Planning , Relative Pose , Visual Servoing , Vertical Oscillation , Center Of Mass , Optimal Control , Fast Fourier Transform , High Altitude , Constant Speed , Unmanned Aerial Vehicles , Inertial Measurement Unit , Pose Estimation , Landing Pad , Vertical Movement , End Of The Trajectory , Discrete Fourier Transform , Optical Flow , Vertical Displacement , Periodic Motion , Touchpoints | |
| dc.title | Vision-based autonomous landing for micro aerial vehicles on targets moving in 3D space | |
| dc.type | Artigo de evento | |
| local.description.resumo | A strategy for autonomous landing of Micro Aerial Vehicles (MAVs) on moving platforms is presented, based only on visual information from a monocular camera. The landing target is uniquely identified by previously known Augmented Reality (AR) markers, and its relative pose is estimated by visual servoing algorithms. Target trajectory in \mathbbR3 is composed of planar translation and vertical oscillation, simulating a vessel that travels in foul weather. The visual feedback helps the aerial robot to track this vessel, while a trajectory planning method, based on the system's model, allows predicting its future pose. Simulated results using the ROS framework are used to verify the effectiveness of our proposed method. | |
| local.publisher.country | Brasil | |
| local.publisher.department | ENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA | |
| local.publisher.initials | UFMG | |
| local.url.externa | https://ieeexplore.ieee.org/document/8981643 |
Arquivos
Licença do pacote
1 - 1 de 1