| Autor: |
Gopikishan Mahto, Smit Kesaria, Kavi Arya, Vikrant Femandes, Manohar Bhat |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
2021 International Symposium of Asian Control Association on Intelligent Robotics and Industrial Automation (IRIA). |
| DOI: |
10.1109/iria53009.2021.9588681 |
| Popis: |
This study showcases a low-resource framework that enables people with no technical know-how to interact with drones, it also explores the capabilities of 2D- computer vision and deep learning techniques for gesture based interface systems on a low-cost micro drone with an onboard RGB camera. This Human-Robot Interaction system processes the real-time human pose to allow a user to command the drone, i.e., by providing direction to move and execute actions. A linear PD controller and image processing techniques are implemented to track humans whilst maintaining a safe distance from the user by perceiving depth information through pose estimation. We incorporated the gesture recognition results into a drone using the Robot Operating System (ROS) and evaluated system performance indoor and outdoor. This low computation framework can be applied further to control robotic arms or mobile robots. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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