Page 9 - Robotics and AI class 10
P. 9

(iv)  Controller for a Robotic System
                      Examples of control systems from daily life: regulation of fan, refrigerator, and air conditioner.
                      Control systems in robotics: Meaning, functions and working; differences between manual and automatic control
                    systems. Block diagrams to be used to illustrate (Input-controller-robot-feedback).
               (v)  Integrating Sensors, Actuators and Controller in a Robotic System
                      Illustration using a simple example: how angular position is measured by a position sensor of a robotic arm is controlled
                    by driving the revolute joint using a motor.
            4.  Visualisation, Design and Creation of Components
               (i)   Application of Mechanical Block of Robotics.
                    Visualise, design and create components of a robot.
                      Using Tinkercad to visualise, design, and create the components of a robot; the different types of joints: revolute and
                    prismatic, RR Mechanism.
               (ii)  Visualisation of motion.
                    Use of Tinkercad to visualise motion of the components designed.
            5.  Integrating Robots as a System
               Building simple robotic systems, wheeled mobile robot, Single Board Computer Coding
                 Using Tinkercad to build simple robotics systems, for example, RR Mechanism. Building simple systems up to a mobile robot
               with four wheels.

                                                            PART II
                                                ARTIFICIAL INTELLIGENCE (AI)

            Note: Key concepts of Class IX need to be revised as a prerequisite.
            1.  Decision making in Machines/ Computers
               (i)   Automated versus Autonomous Systems.
                    Concept of Automated versus Autonomous Systems for Deterministic versus Probabilistic versus.
               (ii)  Decision Making.
                    Human  versus  machine  decision  making  as  subjective  and  objective  respectively;  An  understanding  of  object
                    classification by humans and computers/machines.
               (iii)  Machine Learning (ML).
                    A brief understanding of Machine Learning, role of data and information. Steps in machine learning. Importance of
                    programming and algorithms in teaching machines/computers in subjective decision making.
                    Example such as fruit sorting.
            2.  Machine Intelligence and Cybersecurity in Computing
               (i)   Machine Intelligence – Turing Test.
                    Human Intelligence vs Machine Intelligence; role of the Turing test in AI: a brief understanding only; connectivity
                    between human intelligence and machine intelligence.
               (ii)   Cybersecurity
                    A basic understanding of security and ethical issues such as the unauthorized use of hardware, theft of software,
                    disputed  rights  to  products,  the  use  of  computers  to  commit  fraud,  the  phenomenon  of  hacking  and  data  theft,
                    sabotage in the form of viruses, responsibility for the reliability of output, making false claims for computers, and the
                    degradation of work.
            3.  Components of AI Project Framework
               (i)   Problem Scoping
                    Understanding of problem and finding out which factors affect the problem, defining the goal of the project. The 4 Ws:
                    Who, What, Where, Why. The Problem Statement .
               (ii)  Data Acquisition
                      Types of Data, Data Features, Data Sources, Training and Testing Data and System Maps. Importance of acquiring
                    relevant data from reliable sources.

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