Robotics and Autonomous Systems
Robotics and autonomous systems describe systems of platforms, such as automobiles, airplanes, robots, and UAVs, that move and operate in a physical environment for goal-oriented actions. With the tools and algorithms in multiple toolboxes, you can simulate, estimate, navigate, and control the platform states, such as its position and velocity, as well as monitor the physical environment. Specifically, you can:
Design, model, and simulate autonomous system scenarios that include platforms, trajectories, paths, sensors, and environment using various coordinate systems and maps.
Generate and classify detections, estimate platforms, and obtain various maps of the environment.
Plan the paths of robots, UAVs, and automobiles using different path planning algorithms based on varied motion characteristics.
Control robots, UAVs, and automobiles using multiple motion control algorithms and strategies.
Connect to robots and simulators through middleware (e.g. ROS) and deploy your designed estimation, navigation, and control algorithms on hardware.
Products for Robotics and Autonomous Systems
Topics
Scenario Design and Simulation
- Create Simple RoadRunner Scene (RoadRunner)
Use RoadRunner scene editing software to create a simple road network. - 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. - Simulate Simple Flight Scenario and Sensor in Unreal Engine Environment (UAV Toolbox)
Visualize sensors in a simulation environment that uses Unreal Engine® from Epic Games®.
Simultaneous Localization and Mapping (SLAM)
- Build a Map with Lidar Odometry and Mapping (LOAM) Using Unreal Engine Simulation (Automated Driving Toolbox)
This example shows how to build a map with the lidar odometry and mapping (LOAM) [1] (Automated Driving Toolbox) algorithm by using synthetic lidar data from the Unreal Engine® simulation environment. - Stereo Visual SLAM for UAV Navigation in 3D Simulation (UAV Toolbox)
Generate a map for a city block scene in an Unreal Engine environment using stereo visual simultaneous localization and mapping. - Build a Map from Lidar Data Using SLAM (Navigation Toolbox)
Process 3-D lidar data from a sensor on a vehicle to progressively build a map and estimate the trajectory using SLAM. (Since R2024a) - Monocular Visual-Inertial Odometry (VIO) Using Factor Graph (Navigation Toolbox)
Implement monocular visual-inertial odometry to localize a UAV using camera and IMU data, optimized by a factor graph. (Since R2023b)
Situational Awareness and State Estimation
- 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. - Visual-Inertial Odometry Using Synthetic Data (Sensor Fusion and Tracking Toolbox)
Estimate the pose (position and orientation) of a ground vehicle using an inertial measurement unit (IMU) and a monocular camera.
Motion Planning
- 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. (Since R2021b) - 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®.
Motion Control
- Highway Lane Following with RoadRunner Scene (Automated Driving Toolbox)
Simulate a highway lane following application using a scene created in the RoadRunner 3D scene editing tool. - Path Following with Obstacle Avoidance in Simulink® (Navigation Toolbox)
Use Simulink to avoid obstacles while following a path for a differential drive robot. - Simulate Earth Moving with Autonomous Excavator in Construction Site (Robotics System Toolbox)
Simulate ground excavation to create a depression and move spoil to dump truck and further relocate it to another site. (Since R2024b)
Hardware Deployment
- Scenario Simulation and Flight Visualization with PX4 Hardware-in-the-Loop (HITL) and UAV Dynamics in Simulink (UAV Toolbox)
This example demonstrates 3D scenario Simulation and Flight visualization with PX4® Hardware-in-the-Loop (HITL) and UAV Dynamics contained in Simulink®. - Estimating Orientation Using Inertial Sensor Fusion and MPU-9250 (Sensor Fusion and Tracking Toolbox)
Obtain 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. - Localize TurtleBot Using Monte Carlo Localization Algorithm (Navigation Toolbox)
Apply the Monte Carlo Localization algorithm on a TurtleBot® robot in a simulated Gazebo® environment.
ROS Data and Network Analysis
- Get Started with ROS 2 Network Analyzer App (ROS Toolbox)
Use ROS 2 Network Analyzer app to visualize and analyze nodes, topics, services and actions interaction in ROS 2 network. (Since R2024b) - 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.