Abstract
The paper mainly studied the solution for autonomous control of drone to fly through a rotating obstacle using onboard sensing and computing sources. Especially, the indoor environment is considered, where the global positioning system (GPS) signal is not available. For the estimation of the position of the quadrotor, we proposed the solution based a NVIDIA camera T265 for high-precision and small-delay locating. The real-time detection of the rotating obstacle is achieved by a monocular color camera. First, the histogram equalization technique is implemented to enhance the details of the obstacle, then the color feature is used to detect the target, and finally the angular velocity of the rotating obstacle is estimated by each time it appears at a specific location in the image. The PID controllers with proper gains are adopted for the position and attitude control of our drone. The gains of the attitude controller are tuned first, and after the quadrotor can track the desired attitude angle well, the parameters of the position control are tuned. The results of preliminary experiment show that our drone can estimate its own attitude and position indoors through a binocular camera, and that the angular position and angular velocity of the rotating obstacle are well estimated via the proposed detection algorithm. The overall solution, including the cascade PID controllers, is finally verified in Gazebo simulator.
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Chen, W., Wang, Z., Luo, D., Zhu, B., Peng, C. (2022). Onboard Sensing for Drone to Fly Through a Gate with a Rotating Arm. In: Yan, L., Duan, H., Yu, X. (eds) Advances in Guidance, Navigation and Control . Lecture Notes in Electrical Engineering, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-15-8155-7_134
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DOI: https://doi.org/10.1007/978-981-15-8155-7_134
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