Module #1 Introduction to Robotic Perception and Control Overview of robotic perception and control systems, importance, and applications
Module #2 Robotics Fundamentals Brief review of robotics basics, including kinematics, dynamics, and motion planning
Module #3 Sensors in Robotics Overview of different types of sensors used in robotics, including cameras, lidars, and ultrasonic sensors
Module #4 Image Processing for Robotics Introduction to image processing concepts and techniques for robotic applications
Module #5 Computer Vision for Robotics Introduction to computer vision concepts and techniques for robotic applications
Module #6 Sensor Fusion Combining data from multiple sensors to improve perception and decision-making in robots
Module #7 Perception and Mapping Creating and updating maps of the environment using perception data
Module #8 State Estimation Estimating the state of the robot and its environment using perception data
Module #9 Control Systems Fundamentals Introduction to control systems, including closed-loop and open-loop control
Module #10 Feedback Control Designing and implementing feedback control systems for robots
Module #11 Motion Planning and Control Planning and controlling motion for robots, including trajectory planning and control
Module #12 Robot Arm Control Controlling robot arms, including forward and inverse kinematics
Module #13 Wheeled Mobile Robots Controlling wheeled mobile robots, including motion planning and control
Module #14 Aerial Robots Controlling aerial robots, including quadcopters and UAVs
Module #15 Human-Robot Interaction Designing and implementing human-robot interaction systems, including natural language processing and speech recognition
Module #16 Machine Learning for Robotics Introduction to machine learning concepts and techniques for robotic applications
Module #17 Deep Learning for Robotics Introduction to deep learning concepts and techniques for robotic applications
Module #18 Reinforcement Learning for Robotics Introduction to reinforcement learning concepts and techniques for robotic applications
Module #19 Robustness and Fault Tolerance Designing and implementing robust and fault-tolerant robotic systems
Module #20 Real-Time Systems Designing and implementing real-time systems for robotics, including scheduling and synchronization
Module #21 Robot Operating System (ROS) Introduction to ROS and its applications in robotics
Module #22 Sensorimotor Contingency Theory Introduction to sensorimotor contingency theory and its applications in robotics
Module #23 Autonomy and Decision-Making Designing and implementing autonomous decision-making systems for robots
Module #24 Ethics and Societal Impact Exploring the ethics and societal impact of robotic perception and control systems
Module #25 Course Wrap-Up & Conclusion Planning next steps in Robotic Perception and Control Systems career
