| Proj No. | A2012-251 |
| Title | Vision-based gesture control of drones |
| Summary | The control of drones is traditionally achieved using a remote control. In the last decade, glove-based control was implemented. In this approach, a special glove equipped with sensors, typically inertia measurement units, allows control to be realized simply through hand gestures. However, the need to have a specially designed glove presents a major drawback. In recent years, computer vision based gesture control of drones has attracted considerable attention. The method is simple and cost-effective as no special equipment is needed. Since most if not all drones are equipped with cameras, the camera on a drone just need to take a picture or video of the hand gesture, which is mapped to a specific drone command. The visual data are analyzed using artificial intelligence algorithms and the decision reached is used to execute the required control command. In this project, the student will continue to work on our current vision-based drone control project. A tentative focus is on video stream analysis. Background in python and AI model training is preferred. |
| Supervisor | A/P Ang Diing Shenp (Loc:S2 > S2 B2C > S2 B2C 95, Ext: +65 67906023) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Semiconductor Characterizatio (Loc: S1-B3C-27A) |
| Single/Group: | Single |
| Area: | Smart Electronics and IC design |
| ISP/RI/SMP/SCP?: |