Robotics and Automation using MATLAB and Simulink

Simulink Basics

• Simulink environment and library blocks
• Building and simulating system models
• Solver settings and simulation tuning
• Integrating MATLAB scripts with Simulink

Control Systems for Automation

• PID controllers and closed-loop systems
• Simulating motor control and signal feedback
• Visualization of control response

Hands-On Exercise:

• Design a PID-controlled DC motor system in Simulink
• Simulate an automated conveyor or pick-and-place process

Robotics Basics

• Robotics concepts: DOF, kinematics, and dynamics
• Using Robotics System Toolbox in MATLAB
• Homogeneous transformations and coordinate frames

Robot Motion and Trajectory Planning

• Joint-space vs task-space trajectories
• Trajectory generation and motion visualization in 2D/3D

Hands-On Exercise:

• Simulate a robotic arm performing pick-and-place tasks
• Plot joint angles, end-effector paths, and velocities.

Computer Vision for Automation

• Image acquisition using laptop camera
• Image processing: filtering, edge detection, feature extraction
• Object detection using pre-trained models

Automation Applications

• Vision-based monitoring and task triggering
• Integrating camera input with simulated robotic actions

Hands-On Exercise:

• Detect objects with the camera and simulate automated pick-and-place
• Track object movement and generate control signals

Path Planning and Obstacle Avoidance

• Motion planning algorithms for automation
• Obstacle detection and avoidance in simulation

AI and Machine Learning for Automation

• Using machine learning for decision-making in automated tasks
• Neural networks for control or object classification

Collaborative Robotics Simulation

• Simulating multiple robotic arms or agents
• Coordinated task execution in MATLAB

Hands-On Exercise:

• Path planning and multi-robot task simulation

Automation Workflow Simulation

• End-to-end simulation
• Robotic arm trajectory planning
• Sensor signal emulation (virtual sensors in MATLAB/Simulink)
• Automated task execution based on simulated sensor inputs
• Visualization of the complete system operation

Capstone Project

• Build a complete virtual automated system:
  • Robotic manipulator performing a sequence of tasks
  • Obstacle avoidance and path planning
  • Task scheduling and coordination (multi-robot if desired)
• Generate plots, animations, and performance metrics
• Present simulation workflow and results

Hands-On Exercise:

• Simulate a robotic arm performing a fully automated pick-and-place operation
• Add virtual sensors and control logic to mimic industrial automation

Additional Notes:

• Daily Q&A Sessions
• Regular Assignments
• Final Assessment

Note: Hands-on training will be conducted during the sessions using the tools listed above, subject to availability.