Development of Tracking and Control System Based on Computer Vision for RoboMaster Competition Robot
Xinyang Tang, Chuntao Leng, Yiheng Guan, Hao Li, Shukun Wu
- Year
- 2020
- Citations
- 4
Abstract
In this paper, we present a tracking and control system used to auto-aiming and shooting some given targets. By combining the traditional computer vision method and the neutral network method, our detection for some specific objects achieves real-time (100fps+) and it is robust enough to work on most normal situations. To achieve better performance in shooting moving targets, we fuse the IMU data to do the motion prediction. This makes the system outperforms the human players in hit rate. This system is applied for the RoboMaster competition as an aim-support system and shows good results.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002