✅作者简介热爱科研的Matlab仿真开发者擅长毕业设计辅导、数学建模、数据处理、算法改进、程序设计科研仿真。完整代码获取 定制创新 论文复现私信个人信条做科研博学之、审问之、慎思之、明辨之、笃行之是为博学慎思明辨笃行。 内容介绍基于缓冲的不确定性感知沃罗诺伊单元Buffered Uncertainty-Aware Voronoi CellBUA-VC多机器人碰撞规避是一种用于多机器人系统中动态避碰的方法。具体介绍如下核心原理该方法结合了 Voronoi 图的几何特性与机器人运动的不确定性建模通过扩展传统 Voronoi 单元边界来确保安全距离。先量化 “不确定性”通过感知误差建模和动态障碍物概率预测确定机器人的感知误差及动态障碍物的位置范围等。然后将传统 Voronoi 单元的边界 “向外扩展” 一个由 “机器人自身感知误差 相邻机器人感知误差 动态障碍物预测范围” 组成的 “缓冲距离”构建缓冲 Voronoi 单元形成碰撞避免的 “安全间隙”。并且缓冲 Voronoi 单元会根据场景实时调整如误差变大时缓冲区扩大动态障碍物靠近时优先避让任务紧急时优化缓冲策略等。优势该方法具有概率安全保证通过统计学方法量化碰撞风险优于固定距离的几何方法具备动态适应性可实时更新缓冲距离适应机器人运动状态的变化计算高效基于 Voronoi 图的局部性质仅需邻域机器人信息即可更新单元。应用场景适用于高动态、传感器噪声显著的环境如物流仓库中 AGV 机器人搬运场景、工厂车间中协作机器人同步作业场景以及室外无人机集群巡检场景等。⛳️ 运行结果 部分代码%% initialization script% common pre-run set up for simulation and experiment%% Setup pathsetPath;%% Problem setupglobal pr% environment dimensionpr.dim mode_dim; % problem dimensionxdim [-5, 5]; % workspaceydim [-5, 5];zdim [ 0, 3];if pr.dim 2pr.ws [xdim; ydim];elseif pr.dim 3zdim [0, 10];pr.ws [xdim; ydim; zdim];end% robot physicspr.robot_type 0; % robot typepr.radius 0.2; % robot radiuspr.maxSpeed 0.4; % robot maximal speedpr.boundLocalRadius 2.0; % local bound radius, m% simulation setuppr.dtSim 0.1; % time step, spr.N 10; % number of stagepr.ifSimRobotNoise 1; % if simulating measurement noisepr.ifSimBoxObsNoise 1;% collision probability thresholdpr.collision_probability 0.10;pr.collision_parameter erfinv(2*sqrt(1-pr.collision_probability) - 1);% BVC or BUAVCpr.method mode_region; % 0 - BVC; 1 - BUAVCif pr.ifSimRobotNoise 0pr.method 0;fprintf(Simulate robot localization noise: No. \n);fprintf(Computation of safe region: BVC. \n);elsefprintf(Simulate robot localization noise: Yes. \n);if pr.method 0fprintf(Computation of safe region: BVC. \n);elseif pr.method 1fprintf(Computation of safe region: BUAVC. \n);elseerror(Safe region mode is not defined!);endendpr.control mode_control; % 0 - one-step; 1 - mpcif pr.control 0fprintf(Controller mode: Feedback reactive. \n);elseif pr.control 1fprintf(Controller mode: MPC. \n);elseerror(Controller mode is not defined!);end% weightspr.weights [0.0, 0.0; 1.0, 0.0]; % w_pos, w_input, stage and terminal weights%% Simulation configurationglobal cfg% visualization setupcfg.ifShowHistoryTra 1; % if plotting the history trajectory of the robotcfg.ifShowSafeRegion 1; % if plotting the obstacle-free safe region for each robotcfg.ifShowVelocity 0; % if plotting robot velocity%% Scenario setup% static obstaclesif pr.dim 2vert_m 4;[nBoxObs, boxPos, boxSize, boxYaw] box_initial_2D(3);elseif pr.dim 3vert_m 8;[nBoxObs, boxPos, boxSize, boxYaw] box_initial_3D(3);endboxVert zeros(pr.dim, vert_m, nBoxObs);for iBox 1 : nBoxObs[temp_vert, ~] box2PolyVertsCons(pr.dim, boxPos(:, iBox), ...boxSize(:, iBox), boxYaw(:, iBox));boxVert(:, :, iBox) temp_vert; % dim * m * nBoxObsend% multiple robot, robot initial and end position should not collide with each other and with obstaclesnRobot 5; % number of robotscollision_mtx ones(nRobot, nRobotnBoxObs);while (sum(sum(collision_mtx)) 0)fprintf(Generating robot initial positions and goals ... \n);if pr.dim 2robotStartPos robotStartPos_2D(nRobot, 3, pr.ws(1,:), pr.ws(2,:), pr.radius);% robotEndPos robotStartPos_2D(nRobot, 2, pr.ws(1,:), pr.ws(2,:), pr.radius);robotEndPos -robotStartPos; % robot final goal positionelseif pr.dim 3robotStartPos robotStartPos_3D(nRobot, 2, pr.ws(1,:), pr.ws(2,:), pr.ws(3,:), pr.radius);robotEndPos(1:2, :) -robotStartPos(1:2, :); % robot final goal positionrobotEndPos(3, :) zdim(1) zdim(2) - robotStartPos(3, :);endcollision_mtx_start collision_check(nRobot, nBoxObs, robotStartPos, 1.2*pr.radius, boxVert);collision_mtx_end collision_check(nRobot, nBoxObs, robotEndPos, 1.2*pr.radius, boxVert);collision_mtx [collision_mtx_start; collision_mtx_end];end% robot localization measurement noiserobotPosNoise zeros(pr.dim, pr.dim, nRobot);for iRobot 1 : nRobotrobotPosNoise(:, :, iRobot) 0.10^2 * eye(pr.dim);end% obs localization measurment noiseboxPosNoise zeros(pr.dim, pr.dim, nBoxObs);for iBox 1 : nBoxObsboxPosNoise(:, :, iBox) 0.10^2 * eye(pr.dim);endpr.nRobot nRobot;pr.robotStartPos robotStartPos;pr.robotEndPos robotEndPos;pr.robotPosNoise robotPosNoise;pr.nBoxObs nBoxObs;pr.boxPos boxPos;pr.boxSize boxSize;pr.boxYaw boxYaw;pr.boxPosNoise boxPosNoise;%% For mpcsi_mpc_setup; 参考文献更多免费数学建模和仿真教程关注领取
【机器人】基于缓冲的不确定性感知沃罗诺伊单元多机器人碰撞规避附Matlab代码
发布时间：2026/7/5 1:34:44
✅作者简介热爱科研的Matlab仿真开发者擅长毕业设计辅导、数学建模、数据处理、算法改进、程序设计科研仿真。完整代码获取 定制创新 论文复现私信个人信条做科研博学之、审问之、慎思之、明辨之、笃行之是为博学慎思明辨笃行。 内容介绍基于缓冲的不确定性感知沃罗诺伊单元Buffered Uncertainty-Aware Voronoi CellBUA-VC多机器人碰撞规避是一种用于多机器人系统中动态避碰的方法。具体介绍如下核心原理该方法结合了 Voronoi 图的几何特性与机器人运动的不确定性建模通过扩展传统 Voronoi 单元边界来确保安全距离。先量化 “不确定性”通过感知误差建模和动态障碍物概率预测确定机器人的感知误差及动态障碍物的位置范围等。然后将传统 Voronoi 单元的边界 “向外扩展” 一个由 “机器人自身感知误差 相邻机器人感知误差 动态障碍物预测范围” 组成的 “缓冲距离”构建缓冲 Voronoi 单元形成碰撞避免的 “安全间隙”。并且缓冲 Voronoi 单元会根据场景实时调整如误差变大时缓冲区扩大动态障碍物靠近时优先避让任务紧急时优化缓冲策略等。优势该方法具有概率安全保证通过统计学方法量化碰撞风险优于固定距离的几何方法具备动态适应性可实时更新缓冲距离适应机器人运动状态的变化计算高效基于 Voronoi 图的局部性质仅需邻域机器人信息即可更新单元。应用场景适用于高动态、传感器噪声显著的环境如物流仓库中 AGV 机器人搬运场景、工厂车间中协作机器人同步作业场景以及室外无人机集群巡检场景等。⛳️ 运行结果 部分代码%% initialization script% common pre-run set up for simulation and experiment%% Setup pathsetPath;%% Problem setupglobal pr% environment dimensionpr.dim mode_dim; % problem dimensionxdim [-5, 5]; % workspaceydim [-5, 5];zdim [ 0, 3];if pr.dim 2pr.ws [xdim; ydim];elseif pr.dim 3zdim [0, 10];pr.ws [xdim; ydim; zdim];end% robot physicspr.robot_type 0; % robot typepr.radius 0.2; % robot radiuspr.maxSpeed 0.4; % robot maximal speedpr.boundLocalRadius 2.0; % local bound radius, m% simulation setuppr.dtSim 0.1; % time step, spr.N 10; % number of stagepr.ifSimRobotNoise 1; % if simulating measurement noisepr.ifSimBoxObsNoise 1;% collision probability thresholdpr.collision_probability 0.10;pr.collision_parameter erfinv(2*sqrt(1-pr.collision_probability) - 1);% BVC or BUAVCpr.method mode_region; % 0 - BVC; 1 - BUAVCif pr.ifSimRobotNoise 0pr.method 0;fprintf(Simulate robot localization noise: No. \n);fprintf(Computation of safe region: BVC. \n);elsefprintf(Simulate robot localization noise: Yes. \n);if pr.method 0fprintf(Computation of safe region: BVC. \n);elseif pr.method 1fprintf(Computation of safe region: BUAVC. \n);elseerror(Safe region mode is not defined!);endendpr.control mode_control; % 0 - one-step; 1 - mpcif pr.control 0fprintf(Controller mode: Feedback reactive. \n);elseif pr.control 1fprintf(Controller mode: MPC. \n);elseerror(Controller mode is not defined!);end% weightspr.weights [0.0, 0.0; 1.0, 0.0]; % w_pos, w_input, stage and terminal weights%% Simulation configurationglobal cfg% visualization setupcfg.ifShowHistoryTra 1; % if plotting the history trajectory of the robotcfg.ifShowSafeRegion 1; % if plotting the obstacle-free safe region for each robotcfg.ifShowVelocity 0; % if plotting robot velocity%% Scenario setup% static obstaclesif pr.dim 2vert_m 4;[nBoxObs, boxPos, boxSize, boxYaw] box_initial_2D(3);elseif pr.dim 3vert_m 8;[nBoxObs, boxPos, boxSize, boxYaw] box_initial_3D(3);endboxVert zeros(pr.dim, vert_m, nBoxObs);for iBox 1 : nBoxObs[temp_vert, ~] box2PolyVertsCons(pr.dim, boxPos(:, iBox), ...boxSize(:, iBox), boxYaw(:, iBox));boxVert(:, :, iBox) temp_vert; % dim * m * nBoxObsend% multiple robot, robot initial and end position should not collide with each other and with obstaclesnRobot 5; % number of robotscollision_mtx ones(nRobot, nRobotnBoxObs);while (sum(sum(collision_mtx)) 0)fprintf(Generating robot initial positions and goals ... \n);if pr.dim 2robotStartPos robotStartPos_2D(nRobot, 3, pr.ws(1,:), pr.ws(2,:), pr.radius);% robotEndPos robotStartPos_2D(nRobot, 2, pr.ws(1,:), pr.ws(2,:), pr.radius);robotEndPos -robotStartPos; % robot final goal positionelseif pr.dim 3robotStartPos robotStartPos_3D(nRobot, 2, pr.ws(1,:), pr.ws(2,:), pr.ws(3,:), pr.radius);robotEndPos(1:2, :) -robotStartPos(1:2, :); % robot final goal positionrobotEndPos(3, :) zdim(1) zdim(2) - robotStartPos(3, :);endcollision_mtx_start collision_check(nRobot, nBoxObs, robotStartPos, 1.2*pr.radius, boxVert);collision_mtx_end collision_check(nRobot, nBoxObs, robotEndPos, 1.2*pr.radius, boxVert);collision_mtx [collision_mtx_start; collision_mtx_end];end% robot localization measurement noiserobotPosNoise zeros(pr.dim, pr.dim, nRobot);for iRobot 1 : nRobotrobotPosNoise(:, :, iRobot) 0.10^2 * eye(pr.dim);end% obs localization measurment noiseboxPosNoise zeros(pr.dim, pr.dim, nBoxObs);for iBox 1 : nBoxObsboxPosNoise(:, :, iBox) 0.10^2 * eye(pr.dim);endpr.nRobot nRobot;pr.robotStartPos robotStartPos;pr.robotEndPos robotEndPos;pr.robotPosNoise robotPosNoise;pr.nBoxObs nBoxObs;pr.boxPos boxPos;pr.boxSize boxSize;pr.boxYaw boxYaw;pr.boxPosNoise boxPosNoise;%% For mpcsi_mpc_setup; 参考文献更多免费数学建模和仿真教程关注领取
