Dynamic Target Tracking and Obstacle Avoidance using a Drone
This paper focuses on tracking dynamic targets using a low cost, commercially available drone. The approach presented utilizes a computationally simple potential field controller expanded to operate not only on relative positions, but also relative velocities. A brief background on potential field methods is given, and the design and implementation of the proposed controller is presented. Experimental results using an external motion capture system for localization demonstrate the ability of the drone to track a dynamic target in real time as well as avoid obstacles in its way.
The authors would like to specially thank the Motion Analysis Corporation for their support of the Motion Tracking System (MTS) setup at the Advanced Robotics and Automation (ARA) Lab at the University of Nevada, Reno. This project is partially supported by University of Nevada, Reno and NSF-NRI grant number 1426828.
- 1.Motion analysis systems. http://www.motionanalysis.com
- 2.Shaohua, M., Jinwu, X., Zhangping, L.: Navigation of micro aerial vehicle in unknown environments. In: 2013 25th Chinese Control and Decision Conference (CCDC), pp. 322–327 (2013)Google Scholar
- 3.Sa, I., Corke, P.: System identification, estimation and control for a cost effective open-source quadcopter. In: 2012 IEEE International Conference on Robotics and Automation (ICRA), pp. 2202–2209, May 2012Google Scholar
- 4.Shen, S., Michael, N., Kumar, V.: Autonomous multi-floor indoor navigation with a computationally constrained mav. In: 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 20–25, May 2011Google Scholar
- 7.Shen, S., Michael, N., Kumar, V.: Autonomous indoor 3d exploration with a micro-aerial vehicle. In: 2012 IEEE International Conference on Robotics and Automation (ICRA), pp. 9–15 (2012)Google Scholar
- 14.Mellinger, D., Kumar, V.: Minimum snap trajectory generation and control for quadrotors. In: 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 2520–2525, May 2011Google Scholar
- 15.La, H.M., Lim, R.S., Sheng, W., Chen, J.: Cooperative flocking and learning in multi-robot systems for predator avoidance. In: 2013 IEEE 3rd Annual International Conference on Cyber Technology in Automation, Control and Intelligent Systems (CYBER), pp. 337–342, May 2013Google Scholar
- 18.Woods, A.C.: Dynamic target tracking with ardrone. https://youtu.be/v85hs8-uc1s