Robotics researchers and engineers use MATLAB® and Simulink® to design, simulate, and verify every aspect of autonomous systems, from perception to motion.
Robotics and Autonomous Systems Humanoids Information
Create a 3D physical model or an electromechanical model of autonomous vehicles, drones, and manipulators for simulation, optimization, and reinforcement learning of control algorithms.
Implement sensor data processing algorithms with powerful toolboxes in MATLAB and Simulink.
Use built-in interactive MATLAB apps to implement algorithms for object detection and tracking, localization and mapping.
Use an actively maintained algorithm library to implement 2D or 3D path planning for a robot that is either defined as a point mass or a system with kinematic and dynamic constraints. Perform task planning with Stateflow®, defining the conditions and actions needed for decision making in real time.
Use built-in interactive MATLAB apps to analyse the behaviour of complex systems in time and frequency domains. Design feedback controllers in the deterministic approach, optimization approach, or reinforcement learning approach.
Deploy autonomous algorithms to ROS-based systems and microcontrollers such as Arduino® and Raspberry Pi™. Communicate with embedded targets via protocols, including CAN, EtherCAT®, 802.11™, TCP/IP, UDP, I2C, SPI, MODBUS®, and Bluetooth®.
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