1. FUNDAMENTALS TO ROBOTICS
2. SENSOR TECHNOLOGIES
CLASSIFICATION OF SENSORS:
-- ACTIVE SENSOR: AN ACTIVE SENSOR HAS A PHYSICAL INPUT, AN ELECTRICAL
OUTPUT, AND AN ELECTRICAL EXCITATION INPUT (I. E., THREE ENERGY PORTS) EXAMPLES: ELECTROMECHANICAL ELEMENT, PHOTOELECTRIC ELEMENT, PIEZOELECTRIC ELEMENT AND THERMOELECTRIC ELEMENT
-- PASSIVE SENSOR: A PASSIVE, OR SELF-GENERATING, SENSOR IS ONE WHICH HAS AN INPUT AND AN OUTPUT (I.E., TWO ENERGY PORTS) EXAMPLES: CAPACITATE ELEMENT, INDUCTIVE ELEMENT AND POTENTIOMETER ELEMENT.
SENSOR CHARACTERIZATION:
-- DETECTION MEANS OF SENSORS:
BIOLOGICAL, CHEMICAL, ELECTRIC, MAGNETIC, OR ELECTROMAGNETIC WAVE, HEAT, TEMPERATURE ETC.
CONVERSION PHENOMENA OF SENSORS:
THERMOELECTRIC, PHOTOELECTRIC, PHOTOMAGNETIC, MAGNETOELECTRIC
ELASTOMAGNETIC, THERMOELASTIC, ELASTOELECTRIC
THERMOMAGNETIC ,THERMO-OPTIC, PHOTOELASTIC, ETC
TECHNOLOGICAL ASPECT OF SENSORS:
AMBIENT CONDITIONS ALLOWED, FULL-SCALE OUTPUT, HYSTERESIS, LINEARITY, MEASURED RANGE, OFFSET, OPERATING LIFE, OVERLOAD CHARACTERISTICS, REPEATABILITY, RESOLUTION, SELECTIVITY, SENSITIVITY, SPEED OF RESPONSE, STABILITY, OTHERS
FUNDAMENTAL CIRCUIT OF SENSORS:
3. ROBOT SENSORS
- FORCE AND TACTILE SENSORS: SENSOR TYPE, TACTILE INFORMATION PROCESSING, INTEGRATION CHALLENGES
- INERTIAL SENSORS, GPS, AND ODOMETRY
- SONAR SENSORS: SONAR PRINCIPLES, WAVEFORMS, TIME OF FLIGHT RANGING,SONAR RINGS
- RANGE SENSORS: RANGE SENSING BASICS, REGISTRATION, NAVIGATION
- 3-D VISION AND RECOGNITION: VISUAL SLAM (SIMULTANEOUS LOCALIZATION AND
MAPPING). RECOGNITION
4. MULTISENSOR DATA FUSION AND INTEGRATION:
- MULTISENSOR FUSION METHODS, MULTISENSOR FUSION AND INTEGRATION ARCHITECTURES,
VARIOUS MULTISENSOR FUSION AND INTEGRATION APPLICATIONS
5. ROBOT CONTROL:
- PRINCIPLES OF ROBOT CONTROL, CATEGORY OF ROBOT CONTROL, JOINT SPACE VERSUS TASK SPACE CONTROL, THE BASIC COMPONENTS OF VISUAL SERVO CONTROL, IMAGE BASED VISUAL SERVO CONTROL,POSITION BASED VISUAL SERVO CONTROL AND TARGET TRACKING SERVO CONTROL
6. Artificial Intelligence and Its Robotics Applications
Basic Concepts AI Related Architectures and Algorithms
Convolutional Neural Networks
Recurrent Neural Networks
1.RNN(Recurrent Neural Networks)
2.LSTM( Long Short Term memory)
R-CNN（Regional Convolutional Neural Networks
1.R-CNN，Fast R-CNN
2.Faster R-CNN
Reinforcement learning
Classification
Q-Learning
Sarsa
Deep Q Net （DQN）
Policy Gradient
Actor Critic
Tools
1.Deep Learning Libraries
2.Distributed Deep Learning
Cloud services

7. INDUSTRIAL PRACTICAL EXAMPLES OF AI ENRICHED ROBOT SENSING AND CONTROL THROUGH PHOTOS AND VIDEO DEMONSTRATIONS.