Abstract
This paper proposed a dynamic RRT algorithm that applied to fixed-wing UAV’s path planning in dynamic three-dimensional environment. The tree structure of the dynamic RRT algorithm was expanded by adopting the constraint equations to satisfy fixed-wing UAV’s actual dynamic constrains. In order to avoid collision with dynamic obstacles, corresponding locations of dynamic obstacles in the time of each step are considered in the algorithm. Also, B-spline was also used to interpolate the resulting optimal path for fixed-wing UAV. As a result, the algorithm could generate a smooth path that satisfy UAV’s dynamic constrains in the three-dimensional environment with static and/or dynamic obstacles. The simulation results showed the effectiveness of proposed dynamic RRT algorithm, indicating that it could be applied to fixed-wing UAV’s path planning in dynamic three-dimensional environment.
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References
Hentschel M, Wagner B (2009) Adaptive path planning for long-term navigation of autonomous mobile robots. In: European conference on mobile robots, Ecmr’09, September. Mlini/dubrovnik, Croatia, pp 23–25
Jolly KG, Sreerama KR, Vijaya Kumar R (2009) A Bezier curve based path planning in a multi-agent robot soccer system without violating the acceleration limits. Robot Auton Syst 57:23–33
ŠKrjanc I, Klančar G (2010) Optimal cooperative collision avoidance between multiple robots based on Bernstein-Bézier curves. Robot Auton Syst 58:1–9
Zheng CG, Xu FJ, et al (2006) Online route planner for unmanned air vehicle navigation in unknown battlefield environment. In: IMACS multiconference on computational engineering in systems applications (CESA). IEEE Press, Beijing, pp 4–6
Kruusmaa M (2003) Global navigation in dynamic environments using case-based reasoning. Auton Robots 14(1):71–91
Medeiros FLL, Silva JDS (2010) A Dijkstra algorithm for fixed-wing UAV motion planning based on terrain elevation. In: da Rocha Costa AC, Vicari RM, Tonidandel F (eds) SBIA 2010. LNAI, vol 6404. Springer, Heidelberg, pp 213–222
Kavraki LE, Svestka P, Latombe JC, Overmars MH (1996) Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Trans Robot Autom 12(4):566–580
Lavalle SM, Kuffner JJ (2000) Rapidly-exploring random tree: progress and prospects. Algorithmic and Computational Robotics: New Directions, New York, pp 293–308
Karaman S, Walter MR, Perez A et al (2011) Anytime motion planning using the RRT*. IEEE international conference on robotics & automation. IEEE Press, Shanghai, pp 1478–1483
Lee D, Song HJ, Shim DH (2014) Optimal path planning based on spline-RRT* for fixed-wing UAVs operating in three-dimensional environments. In: 14th IEEE international conference on control, automation and systems. IEEE Press, Gyeonggi-do, pp 835–839
Shan EZ, Dai B, Song JZ, Sun ZP (2009) An dynamic RRT path planning algorithm based on B-spline. In: 2nd IEEE international symposium on computational intelligence and design. IEEE Press, Changsha, pp 25–29
Yang K, Gan SK, Sukkarich S (2010) An efficient path planning and control algorithm for RUAV’s in unknown and cluttered environments. J Intell Rob Syst 57:101–122
Yao P, Wang HL, Su ZK (2015) Real-time path planning of unmanned aerial vehicle for target tracking and obstacle avoidance in complex dynamic environment. Aerosp Sci Technol 47:269–279
Zhu LH, Cheng XH, Yuan FG (2016) A 3D collision avoidance strategy for UAV with physical constrains. Measurement 77:40–49
Wang WP, Helmut P, Liu Y (2006) Fitting B-spline curves to point clouds by curvature-based squared distance minimization. ACM Trans Graph 25(2):214–238
Kan EM (2010) Radar-aware path planning with B-spline trajectory generation for unmanned aerial vehicles (UAVs). Int J Reasoning-Based Intell Syst 2(3/4):226–236
Kan EM, Lim MH, Yeo SP et al (2011) Contour based path planning with B-spline trajectory generation for unmanned aerial vehicles (UAVs) over hostile terrain. J Intell Learn Syst Appl 03(3):122–130
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Lu, L., Zong, C., Lei, X., Chen, B., Zhao, P. (2017). Fixed-Wing UAV Path Planning in a Dynamic Environment via Dynamic RRT Algorithm. In: Zhang, X., Wang, N., Huang, Y. (eds) Mechanism and Machine Science . ASIAN MMS CCMMS 2016 2016. Lecture Notes in Electrical Engineering, vol 408. Springer, Singapore. https://doi.org/10.1007/978-981-10-2875-5_23
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DOI: https://doi.org/10.1007/978-981-10-2875-5_23
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