Multi-UAV Route Re-Generation Method 
Based on Trajectory Data

doi:10.1007/s12204-021-2332-2

Abstract

Abstract: A large quantity of unmanned aerial vehicle (UAV) trajectory data related to air traffic information has important value in engineering fields. However, the cost of data and trajectory processing limits the applications, and as the number of UAVs increases rapidly, future UAVs’ path data will be very large. Therefore, this paper designs a multi-UAV route re-generation method based on trajectory data, which can realize the UAVs’ path data compression, de-aggregation, and regeneration tasks. Based on the trajectory data, the three-dimensional Douglas-Peucker algorithm is used to compress the trajectory data to reduce the storage space. The improved B-spline path smoothing algorithm based on the reversing control point is used to depolymerize and smooth the path. Simulation experiments show that the above multi-UAV route re-generation algorithm can obtain a more optimized path while maintaining the important characteristics of the original path.

Key words: unmanned aerial vehicle (UAV), trajectory data, route re-generation, three-dimensional Douglas-Peucker algorithm, improved B-spline path smoothing algorithm, reversing control point

CLC Number:

V 279

YUAN Dongdong (袁冬冬), WANG Yankai∗ (王彦恺), BAI Jiaqi (白嘉琪). Multi-UAV Route Re-Generation Method Based on Trajectory Data[J]. J Shanghai Jiaotong Univ Sci, 2022, 27(6): 806-816.

References 22

[1]	KHATIB O. Real-time obstacle avoidance for manipulators and mobile robots [J]. The International Journal of Robotics Research, 1986, 5(1): 396-404.
[2]	SUDHAKARA P, GANAPATHY V, PRIYADHARSHINI B, et al. Obstacle avoidance and navigation planning of a wheeled mobile robot using amended artificial potential field method [J]. Procedia Computer Science, 2018, 133: 998-1004.
[3]	CHEN H, LI Y, LUO J D. Research of mobile robot path planning based on improved A? algorithm optimization [J]. Automation & Instrumentation, 2018 (12): 1-4 (in Chinese).
[4]	LU W L, LEI J S, SHAO Y. Path planning for mobile robot based on an improved A? algorithm [J]. Journal of Ordnance Equipment Engineering, 2019, 40(4): 197-201 (in Chinese).
[5]	JIA G Z. Research on three-dimensional flight path planning of UAV based on genetic algorithm and sparse A? algorithm [D]. Nanjing, China: Nanjing University of Posts and Telecommunications, 2017 (in Chinese).
[6]	NOBAHARI H, POURTAKDOUST S H. An optimalfuzzy two-phase CLOS guidance law design using ant colony optimisation [J]. The Aeronautical Journal, 2007, 111(1124): 621-636.
[7]	BAGHERIAN M, ALOS A. 3D UAV trajectory planning using evolutionary algorithms: A comparison study [J]. The Aeronautical Journal, 2015, 119(1220): 1271-1285.
[8]	BAI Y Z. Three-dimensional path planning based on parameter variance adjustment firefly algorithm [J]. Computer System & Applications, 2015, 24(5): 92-99 (in Chinese).
[9]	CHEN Y, WU K Q, WANG D, et al. Elastic algorithm: A new path planning algorithm about auto-navigation in 3D virtual scene [M]//Advances in artificial reality and tele-existence. Berlin, Heidelberg: Springer, 2006: 1156-1165.
[10]	BRANDT T, SATTEL T. Path planning for automotive collision avoidance based on elastic bands [J]. IFAC Proceedings Volumes, 2005, 38(1): 210-215.
[11]	XING Y X. Research on search and rescue optimization of UAV disaster area based on swarm intelligence algorithm [D]. Dalian, China: Dalian University of Technology, 2019 (in Chinese).
[12]	LI L L. Path planning algorithm for robots based on elastic band theory [D]. Xi’an, China: Xidian University, 2013 (in Chinese).
[13]	HILGERT J, HIRSCH K, BERTRAM T, et al. Emergency path planning for autonomous vehicles using elastic band theory [C]//Proceedings 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Kobe, Japan: IEEE, 2003: 1390-1395.
[14]	ZHANG S K. Data-driven based automatic routing for unmanned ship and surface vehick [D]. Dalian, China: Dalian Maritime University, 2016 (in Chinese).
[15]	ZHAO L B, SHI G Y. A method for simplifying ship trajectory based on improved Douglas-Peucker algorithm [J]. Ocean Engineering, 2018, 166: 37-46.
[16]	ZHAO L B, SHI G Y. A trajectory clustering method based on Douglas-Peucker compression and density for marine traffic pattern recognition [J]. Ocean Engineering, 2019, 172: 456-467.
[17]	DOU S Q. A synchronous simplified method of the river network line vector and DEM based on the three dimensional DP algorithm [D]. Beijing, China: China University of Mining and Technology, Beijing, 2015 (in Chinese).
[18]	DOU S Q, LIU C J, LIN Y W, et al. A method of multibeam echo sounding system data thinning based on improved 3D Douglas-Peucker algorithm [J]. Science & Technology Review, 2014, 32(19): 21-25 (in Chinese).
[19]	SUN R, ZHANG W S. Smooth path planning of mobile robot based on improved ant colony algorithm [J]. Journal of Graphics, 2019, 40(2): 344-350 (in Chinese).
[20]	WANG B R, WANG T, LI Z G, et al. An adaptive look-ahead positioin and orientation interpolation algorithm for multi-path segments smooth transition [J]. Control and Decision, 2019, 34(6): 1211-1218 (in Chinese).
[21]	ELBANHAWI M, SIMIC M, JAZAR R N. Continuous path smoothing for car-like robots using B-spline curves [J]. Journal of Intelligent & Robotic Systems, 2015, 80(1): 23-56.
[22]	SINGH A K, AGGARWAL V, SAXENA P, et al. Performance analysis of trajectory compression algorithms on marine surveillance data [C]//International Conference on Advances in Computing, Communications and Informatics. Udupi, India: IEEE, 2017: 1074-1079.

Multi-UAV Route Re-Generation Method Based on Trajectory Data

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References 22

Related Articles 3

Recommended Articles

Metrics

Comments

[1]	YUAN Dongdong (袁冬冬), WANG Yankai∗ (王彦恺). Data Driven Model-Free Adaptive Control Method for Quadrotor Trajectory Tracking Based on Improved Sliding Mode Algorithm [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(6): 790-798.
[2]	SONG Xueqian* (宋雪倩), HU Shiqiang (胡士强). Hierarchy-Based Adaptive Generalized Predictive Control for Aerial Grasping of a Quadrotor Manipulator [J]. Journal of Shanghai Jiao Tong University (Science), 2019, 24(4): 451-458.
[3]	CHEN Zirong *(陈仔荣), LU Yafei (鲁亚飞), HOU Zhongxi (侯中喜), WANG Junwei (王俊伟). UAV's Coverage Search Planning Algorithm Based on Action Combinations [J]. Journal of Shanghai Jiao Tong University (Science), 2019, 24(1): 48-57.