机器人与自主系统
R2026b机器人与自主系统介绍在物理环境中移动和操作以执行目标导向的动作的平台系统,如汽车、飞机、机器人和无人机。您可以通过多个工具箱中的工具和算法来仿真、估计、导航和控制平台状态(如它们的位置和速度)以及监控物理环境。具体来说,您可以:
使用各种坐标系和地图来设计、建模和仿真自主系统场景,包括平台、轨迹、路径、传感器和环境。
生成检测并进行分类,估计平台,并获得各种环境地图。
基于不同的运动特性,使用不同的路径规划算法来规划机器人、无人机和汽车的路径。
使用多种运动控制算法和策略控制机器人、无人机和汽车。
通过中间件(例如 ROS)连接到机器人和仿真器,并在硬件上部署您设计的估计、导航和控制算法。
适用产品: 机器人与自主系统
Automated Driving Toolbox
Design, simulate, and test ADAS and autonomous driving systems
Robotics System Toolbox
Design, simulate, test, and deploy robotics applications
UAV Toolbox
Design, simulate, and deploy UAV applications
ROS Toolbox
Design, simulate, and deploy ROS-based applications
Sensor Fusion and Tracking Toolbox
Design, simulate, and test multisensor tracking and positioning systems
RoadRunner
设计用于自动驾驶模拟的三维场景
RoadRunner Scenario
Create and play back scenarios for automated driving simulation
Simulink 3D Animation
Simulate and visualize dynamic systems in a 3D environment
主题
越野自主驾驶
- Drive Agricultural Tractor in Vineyard Using Unreal Engine (Robotics System Toolbox)
Drive an agricultural tractor through a vineyard scene in Unreal Engine. (自 R2026b 起) - Generate Synthetic Sensor Data for Localization Using Unreal Engine (Robotics System Toolbox)
Simulate IMU and monocular camera data in Unreal Engine to develop and validate state estimation algorithms. (自 R2026b 起)
场景设计和仿真
- Design a Curved Road Programmatically using MATLAB Scene Authoring Functions (RoadRunner)
Design a curved road using scene authoring functions. - 使用 RoadRunner 高清地图构建具有交叉路口和静态目标的 RoadRunner 场景 (RoadRunner)
使用 RoadRunner 高清地图构建包含道路交叉路口和周围静态目标的 RoadRunner 场景。 - Create Driving Scenario Interactively and Generate Synthetic Sensor Data (Automated Driving Toolbox)
Use the Driving Scenario Designer app to create a driving scenario and generate sensor detections and point cloud data from the scenario. - Generate RoadRunner Scenario from Recorded Sensor Data (Automated Driving Toolbox)
Generate RoadRunner Scenario from recorded GPS data and preprocessed actor track list. - Aerodynamic Parameter Estimation Using Flight Log Data (UAV Toolbox)
Improve the accuracy of a UAV model by using flight log data to estimate the aerodynamic parameters of the UAV.
态势感知和状态估计
- Extended Object Tracking of Highway Vehicles with Radar and Camera (Sensor Fusion and Tracking Toolbox)
Track highway vehicles around an ego vehicle as extended objects that span multiple sensor resolution cells. - Resilient Pose Estimation Using Terrain-Aided Inertial Sensor Fusion in GPS-Denied Environments (Navigation Toolbox)
- IMU and GPS Fusion for Inertial Navigation (Navigation Toolbox)
This example shows how you might build an IMU + GPS fusion algorithm suitable for unmanned aerial vehicles (UAVs) or quadcopters. - Multi-Constellation GNSS Positioning Using RINEX Files (Navigation Toolbox)
Estimate GNSS receiver position using RINEX data from multiple satellite systems for improved accuracy and reliability. (自 R2026a 起)
运动规划和控制
- Object Tracking and Motion Planning Using Frenet Reference Path (Sensor Fusion and Tracking Toolbox)
Dynamically plan the motion of an autonomous vehicle based on estimates of the surrounding environment. - Plan Path for Manipulator in Simulink with Robotics System Toolbox (Robotics System Toolbox)
Simulate manipulator path planning in Simulink® with code generation for autonomy functions from MATLAB®. - Highway Lane Following with RoadRunner Scenario (Automated Driving Toolbox)
Simulate highway lane following application, designed in Simulink, with RoadRunner Scenario.
硬件部署
- Run ArduPilot Software-in-the-Loop Simulation with Quadcopter Plant in Simulink (UAV Toolbox)
Verify a quadcopter controller design by using Software-in-the-Loop (SITL) simulation and simulating the quadcopter plant model in Simulink. - PX4 Hardware-in-the-Loop (HITL) Simulation with Fixed-Wing Plant in Simulink (UAV Toolbox)
This example shows how to use the UAV Toolbox Support Package for PX4® Autopilots to verify the controller design by deploying the design on the PX4 Autopilot hardware board. - Estimating Orientation Using Inertial Sensor Fusion and MPU-9250 (Navigation Toolbox)
This example shows how to get data from an InvenSense MPU-9250 IMU sensor, and to use the 6-axis and 9-axis fusion algorithms in the sensor data to compute orientation of the device. - Sign Following Robot with ROS in MATLAB (ROS Toolbox)
Control a simulated robot running on a separate ROS-based simulator over a ROS network using MATLAB.
ROS 数据和网络分析
- Visualize Messages from Live ROS or ROS 2 Topics (ROS Toolbox)
Visualize messages from live ROS or ROS 2 topics in ROS Data Analyzer app. - Publish Ground Truth and Sensor Data from RoadRunner Scenario to ROS 2 Network (ROS Toolbox)
Publish ground-truth and sensor data from a RoadRunner scenario to ROS 2 network and visualize it using ROS Data Analyzer app. (自 R2025a 起)
精选示例
视频
使用 MATLAB 和 Simulink 开发自主系统
本视频演示了如何开发用于自动驾驶车辆建模与仿真、自动驾驶算法设计、系统虚拟测试以及硬件部署的工作流。
航空航天与国防应用领域的自主技术
本视频介绍了如何为航空航天和国防应用领域(如无人机 (UAV)、无人地面交通工具 (UGV) 和自主水下航行器 (AUV))开发自主技术。
使用 MATLAB 设计和部署协作机器人 (Cobot)
本视频演示了如何使用 Robotic System Toolbox 来设计、仿真、测试和部署机器人应用(包括协作机器人)。
利用 MATLAB 开辟越野自主驾驶之路
本视频探讨了 MATLAB 和 Simulink 如何通过仿真、传感器融合和 HIL 测试,加速越野机械的控制与自动化设计。
为先进的空中交通应用设计和仿真垂直起降 (VTOL) 飞机
本视频展示了如何开发垂直起降 (VTOL) 控制系统和逼真的仿真,以对先进的空中出行任务进行仿真。









