新网站排名优化,西宁微网站建设多少钱,卖做游戏点卡网站创业,政协网站法治建设版块#x1f4a5;#x1f4a5;#x1f49e;#x1f49e;欢迎来到本博客❤️❤️#x1f4a5;#x1f4a5; #x1f3c6;博主优势#xff1a;#x1f31e;#x1f31e;#x1f31e;博客内容尽量做到思维缜密#xff0c;逻辑清晰#xff0c;为了方便读者。 ⛳️座右铭欢迎来到本博客❤️❤️ 博主优势博客内容尽量做到思维缜密逻辑清晰为了方便读者。 ⛳️座右铭行百里者半于九十。 目录 1 概述 2 运行结果 3 参考文献 4 Matlab代码实现 1 概述
船舶运动规划是海上自主水面舰艇MASS自主导航的核心问题。该文提出一种考虑避碰规则的复杂遭遇场景模型预测人工势场MPAPF运动规划方法。建立了一个新的船舶域其中设计了一个闭区间势场函数来表示船舶域的不可侵犯属性。在运动规划过程中采用具有预定义速度的Nomoto模型来生成符合船舶运动学的可遵循路径。为解决传统人工势场APF方法的局部最优问题保证复杂遭遇场景下的防撞安全提出一种基于模型预测策略和人工势场的运动规划方法MPAPF。该方法将船舶运动规划问题转化为具有机动性、导航规则、通航航道等多重约束的非线性优化问题。4个算例的仿真结果表明与APF、A星和快速探索随机树RRT的变体相比所提出的MPAPF算法能够解决上述问题并生成可行的运动路径避免复杂遭遇场景下的船舶碰撞。
文献来源 2 运行结果
输入预测步长我们建议应该是1~10在这个程序中1步可能花费你120秒而10步可能比1步高100倍。 部分代码
%% initialization static_obs_num [12;6]; mailme 0; % static_obs_area [0.8, 2, 7, 8; % 2, 0.2, 10, 2]; static_obs_area [0.5, 0, 4.5, 4; 4.5, 2, 6.5 3.5]; dynamic_ships [1;1;1;1]; parameter.waterspeed 0/1852; parameter.waterangle 45; parameter.water [sind(parameter.waterangle) cosd(parameter.waterangle)]*parameter.waterspeed; parameter.minpotential 0.001; parameter.minpotential4ship 0.01; parameter.minobstacle 0.03; parameter.maxobstacle 0.2; parameter.safeobstacle 5; parameter.amplification 5; parameter.safecv 2.5;%n mile safety collision aviodance distance parameter.dangercv 0.5;% danger collision aviodance distance parameter.shipdomain 5; parameter.tsNum 1; %% simulation environment map_size [8,4.5]; start_point [1 1]; end_point [7,4]; tmp_end_point end_point; parameter.endbeta -log(parameter.minpotential)/(norm(end_point-start_point)*2)^2; mat_point init_obstacles(static_obs_num,static_obs_area); % Generate static obstacles randomly ship.speed 8.23; % meters per second equal to 16 knots ship.v 0; ship.data [... data [ U K T n3] 6 0.08 20 0.4 9 0.18 27 0.6 12 0.23 21 0.3 ]; % interpolate to find K and T as a function of U from MSS toolbox frigate prompt Prediction Step\n; % input the prediction step, 1~10 parameter.prediction_step input(prompt); ship.k interp1(ship.data(:,1),ship.data(:,2),ship.speed,linear,extrap); %ship dynamic model you can change the dynamic model in shipdynamic.m ship.T interp1(ship.data(:,1),ship.data(:,3),ship.speed,linear,extrap); ship.n3 interp1(ship.data(:,1),ship.data(:,4),ship.speed,linear,extrap); ship.Ddelta 10*pi/180; % max rudder rate (rad/s) ship.delta 30*pi/180; % max rudder angle (rad) ship.length 100; ship.p_leader -8; ship.alpha_leader 3; ship.yaw 45; ship.yaw_rate 0; ship.rudder 0; ship.rudder_rate 0; ship.position [1 1]; ship.gamma 1; ship.lamda log(1/parameter.minpotential4ship-1)/((parameter.shipdomain)^2-1); ship.prediction_postion []; tsPath{parameter.tsNum} []; ship1 ship; parameter.scale 1852; % 1852m in real world ,1 in simulation; parameter.time 5; % time per step parameter.searching_step 3000; % max searching step parameter.map_size map_size; % map size for display parameter.map_min 0.05; % minmum map details parameter.end1 0.05; % parameter.situs1 [6.1 1.75 3.25 1.75]; parameter.situs1 [6.1 3.9 3.25 1.75]; % a quaternion ship domain proposed in Wang 2010,situs1 means in head-on situation parameter.situs2 [6.1 3.9 3.25 1.75]; % a quaternion ship domain proposed in Wang 2010,situs2 means in crossing and give-way situation parameter.situs3 [0.0 0.0 0.00 0.00]; % a quaternion ship domain proposed in Wang 2010,situs3 means in crossing and stand-on situation parameter.situs0 [6.0 6.0 1.75 1.75]; % a quaternion ship domain proposed in Wang 2010,situs0 means in norm naviation situation ship_scale 1; leader_stop 0; tic draw2(); set(gcf,position,[200 200 1361/1.5 750/2]); hold on LB_follower []; UB_follower []; for i 1 : parameter.prediction_step LB_follower [LB_follower 0 -ship.delta];% lower limiting value UB_follower [UB_follower 0 ship.delta];% upper limiting value end parameter.navars 2*parameter.prediction_step;% number of navars targetshipinit_ship(ship,others,1000);
3 参考文献
[1]He, Zhibo, et al. “A Novel Model Predictive Artificial Potential Field Based Ship Motion Planning Method Considering COLREGs for Complex Encounter Scenarios.” ISA Transactions, Elsevier BV, Sept. 2022, doi:10.1016/j.isatra.2022.09.007.
4 Matlab代码实现
