Sensor Integration in Robotics
( 24 Modules )

Module #1
Introduction to Sensor Integration
Overview of sensor integration in robotics, importance, and applications

Module #2
Types of Sensors in Robotics
Classification and characteristics of various sensors used in robotics, such as proprioceptive, exteroceptive, and introspective sensors

Module #3
Sensor Fusion Fundamentals
Basic concepts and techniques of sensor fusion, including data fusion, feature fusion, and decision fusion

Module #4
Sensor Calibration and Characterization
Methods for calibrating and characterizing sensors, including intrinsic and extrinsic calibration

Module #5
Analog-to-Digital Conversion
Principles and techniques of analog-to-digital conversion, including sampling and quantization

Module #6
Digital Signal Processing for Sensors
Fundamentals of digital signal processing, including filtering, convolution, and Fourier transforms

Module #7
Sensors for Position and Orientation
Overview of sensors for position and orientation, including GPS, accelerometers, gyroscopes, and magnetometers

Module #8
Sensors for Proximity and Distance
Overview of sensors for proximity and distance, including ultrasonic, infrared, and lidar sensors

Module #9
Sensors for Object Detection and Recognition
Overview of sensors for object detection and recognition, including cameras, lidars, and radar sensors

Module #10
Sensors for Environmental Monitoring
Overview of sensors for environmental monitoring, including temperature, humidity, and gas sensors

Module #11
Sensor Integration Architectures
Overview of sensor integration architectures, including centralised, decentralised, and distributed architectures

Module #12
Middleware for Sensor Integration
Overview of middleware for sensor integration, including ROS, Robot Operating System, and other frameworks

Module #13
Kalman Filter-Based Sensor Fusion
Introduction to Kalman filter-based sensor fusion, including prediction, update, and measurement models

Module #14
Machine Learning for Sensor Integration
Introduction to machine learning for sensor integration, including regression, classification, and clustering

Module #15
Sensor-Based Control Systems
Overview of sensor-based control systems, including feedback control and state estimation

Module #16
Sensor Integration for Mobile Robots
Sensor integration for mobile robots, including navigation, localization, and obstacle avoidance

Module #17
Sensor Integration for Manipulator Robots
Sensor integration for manipulator robots, including grasping, manipulation, and force control

Module #18
Sensor Integration for Human-Robot Interaction
Sensor integration for human-robot interaction, including speech recognition, gesture recognition, and facial recognition

Module #19
Sensor Integration for Autonomous Vehicles
Sensor integration for autonomous vehicles, including perception, motion planning, and control

Module #20
Sensor Integration for Robustness and Fault Tolerance
Sensor integration for robustness and fault tolerance, including redundancy, diversity, and error detection

Module #21
Sensor Integration for Real-Time Systems
Sensor integration for real-time systems, including real-time operating systems and scheduling algorithms

Module #22
Sensor Integration for Cyber-Physical Systems
Sensor integration for cyber-physical systems, including IoT, Industry 4.0, and smart cities

Module #23
Case Studies in Sensor Integration
Real-world case studies in sensor integration, including industrial, service, and social robots

Module #24
Course Wrap-Up & Conclusion
Planning next steps in Sensor Integration in Robotics career

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Sensor Integration in Robotics ( 24 Modules )

Sensor Integration in Robotics
( 24 Modules )