计算机科学 ›› 2017, Vol. 44 ›› Issue (Z11): 72-79.doi: 10.11896/j.issn.1002-137X.2017.11A.014
陈晋音,李玉玮,杜文耀
CHEN Jin-yin, LI Yu-wei and DU Wen-yao
摘要： 随着小型无人机的广泛应用,无人机的自动巡航能力变得至关重要。无人机航迹规划,是指其在已知环境地图信息下展开航迹规划以实现无碰撞地、平滑地从初始点到达目标点。针对现有算法依然存在收敛速度慢、遍历时间长和航迹曲线化无法满足实际无人机飞行条件等问题,首先提出了EB-RRT*(Efficient B-RRT*)算法,设计自适应避障提高算法收敛速度并减少内存占用；然后采用栅格分区的方法缩短附近节点的遍历时间；最后利用合理的降采样和三次贝塞尔插值算法对折点进行光滑化的处理,使算法最终生成相对平滑的航迹,为无人机实际飞行提供可行航迹规划方法。进行了多组不同环境复杂度的实验,并将该算法与其他算法进行对比,结果验证了所提算法的有效性。
| [1] VALAVANIS K P.Advances in unmanned aerial vehicles[M]∥State of Art and Road to Autonomy.2007. [2] DE A,CAVES J.Human-automation collaborative RRT for UAVmission path planning[M]∥Massachusetts Institute of Technology,2010. [3] TRIHARMINTO H H,PRABUWONO A S.UAV DynamicPath Planning for Intercepting of a Moving Target:A Review[J].Communications in Computer and Information Science,2013,376:206-219. [4] HOLLAND J H.Adaptation in natural and artificial systems[M].MIT Press,1992. [5] ROBERGE V,TARBOUCHI M,LABONTE G.Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real Time UAV Path Planning[J].IEEE Transactions on Industrial Informatics,2013,9(1):132-141. [6] KAVRAKI L,SVESTKA P.Probabilistic roadmaps for pathplanning in high-dimensional configuration spaces[J].IEEE Transactions on Robotics & Automations,1996,12(4):566-580. [7] LAVALLE S M,KUFFNER J J.Randomized KinodynamicPlanning[J].IEEE International Conference on Robotics & Automation,1999,1(5):473-479. [8] MELCHIOR N A,SIMMONS R.Particle RRT for Path Planning with Uncertainty[C]∥IEEE International Conference on Robotics & Automation.2007:1617-1624. [9] LINDEMANN S R,LAVALLE S M.Incrementally reducing dis-persion by increasing voronoi bias in rrts[J].IEEE International Conference on Robotics & Automation,2004,4(4):3251-3257. [10] KARAMAN S,FRAZZOLI E.Incremental sampling-based algorithms for optimal motion planning[J].International Journal of Robotics Research,2010,30(7):2011. [11] QURESHI A H,MUMTAZ S,IQBAL K F,et al.Triangular geo-metry based optimal motion planning using RRT*-motion planner[C]∥IEEE International Workshop on Advanced Motion Control.2014:380-385. [12] KUFFNER J J,LAVALLE S M.RRT-connect:An efficient approach to single-query path planning[C]∥IEEE International Conference on Robotics and Automation.2000:995-1001. [13] JORDAN M,PEREZ A.Optimal Bidirectional Rapidly-Exploring Random Trees:MIT-CSAIL-TR-2013-021[R].2013. [14] ZHANG X,LüTTEKE F,ZIEGLER C,et al.Self-learning RRT* Algorithm for Mobile Robot Motion Planning in Complex Environments[M]∥Intelligent Autonomous Systems 13,2016:57-69. [15] BAIZID K,CHELLALI R,LUZA R,et al.RRS:Rapidly-Exploring Random Snakes a New Method for Mobile Robot Path Planning[M]∥Intelligent Autonomous Systems 13.Springer International Publishing,2014:291-305. [16] XIONG J,HU Y,WU B,et al.Minimum-cost rapid-growing randomtrees for segmented assembly path planning[J].The International Journal of Advanced Manufacturing Technology,2015,77(5):1043-1055. [17] YANG K.An efficient Spline-based RRT path planner for non-holonomic robots in cluttered environments[C]∥International Conference on Unmanned Aircraft Systems.2013:288-297. [18] ABBADI A,PRENOSIL V.Collided Path Replanning in Dyna-mic Environments Using RRT and Cell Decomposition Algorithms[M]∥Modelling and Simulation for Autonomous Systems.Springer International Publishing,2015:131-143. |
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