Robotics and AI Book for Class 10 – ICSE Subject Code 66


Discover Robotics and AI with the Class 10 ICSE curriculum book (Code 66). This comprehensive guide offers hands-on learning in Robotics, Artificial Intelligence, Machine Learning, and Python Programming. The book is structured into four parts, encompassing theoretical knowledge, practical lab activities using PictoBlox and Quarky, and project-based learning.

  • Education Board Alignement – ICSE
  • Number of Pages – 233
  • Number of Chapters – Robotics Specific Skills – 5
  • Number of Chapters – Artificial Intelligence Specific Skills – 4
  • Number of Lab Activities – 40
  • Software and Hardware Used – Windows 10, PictoBlox Python, PictoBlox AI, PictoBlox Machine Learning Environment
  • Competition – Access to Codeavour – The global AI, Coding and Robotics championship to foster creativity, innovation and entrepreneurial skills among students of age 7 to 18 years to raise awareness about UN Sustainable Development Goals.
  • Technologies Covered – Robotics, Artificial Intelligence, Data Science and Machine Learning
  • Certification – Submit 15 lab activities online to get digital certificate accredited by STEMpedia, and ARTPARK.

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Empowering Kids with the Right Future Skills

The ICSE Class 10 Robotics and AI curriculum provides students with foundational knowledge and practical skills in Robotics and AI, preparing them for a future in our technologically evolving world.

Quarky line following robot

Hands-on Robotics

Quarky Robotic Arm with pick-and-place function

Industrial Robotics

Machine Learning

Quarky line following robot

Hands on Robotics

Quarky Robotic Arm with pick-and-place function

Industrial Robotics

Machine Learning

Artificial Intelligence

Kid engaged in Python programming on PictoBlox

Python Programming

AI Project cycle including 5 steps - Problem Scoping, Data Acquisition, Data Exploration, Modelling, and Evaluation.

AI Project Cycle

Artificial Intelligence

Kid engaged in Python programming on PictoBlox

Python Programming

AI Project cycle including 5 steps - Problem Scoping, Data Acquisition, Data Exploration, Modelling, and Evaluation.

AI Project Cycle

Inside the Book

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ICSE Curriculum Aligned

Tailored for Class 10, this book aligns with the ICSE curriculum in Robotics and AI (Code 66), ensuring comprehensive and relevant educational content.

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Thorough Coverage of Robotics and AI

It covers essential topics in Robotics, AI, Python programming, and machine learning, making it a complete resource for students.

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Activity-Based Learning

Incorporating 40 hands-on activities and theme-based learning that make learning both fun and intellectually stimulating.

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Future-Ready Education Focus

Designed to prepare students for a technologically advanced future, it equips them with skills and knowledge essential for upcoming technological challenges.

Icon of PictoBlox

PictoBlox AI Software

Learn the art of coding through Python coding in PictoBlox, a premier tool for young learners. Students also receive 5000 AI credits for PictoBlox.

Badge for Certificate

Codeavour Competition

Exclusive access to Codeavour – the AI and Robotics Competition, with the opportunity to represent India on the global stage at Dubai.

Software and Hardware Used

Windows 10

Quarky Robot

PictoBlox Python Coding

PictoBlox AI

PictoBlox Machine Learning

Part 1 - Robotics Skills

This section e xplores the evolution and impact of New Age Robotic Systems (NARS) across various industries, the transition from robots to cobots, components of robotic systems, and practical assembly and programming of different types of robots.

Part 1 - Unit 1 - New Age Robotic Systems

Unit 1: New Age Robotic Systems

  • Section 1: Explores the evolution and modern impact of New Age Robotic Systems (NARS), differentiating them from traditional robotics.
  • Section 2: Examines the role of robots in logistics and supply chain management, with future trends in warehouse automation.
  • Section 3: Discusses assistant robots in daily life, including ethical aspects and human-robot interaction.
  • Section 4: Focuses on the integration of robotics in smart environments such as homes, schools, and mobility solutions.
  • Section 5: Covers the diverse industrial applications of autonomous drones.
  • Section 6: Highlights the advancements and future prospects of robotics in medicine and healthcare.
  • Section 7: Explores the use of robotics in agriculture, construction, and other industries, including modern elevator systems.
  • Section 8: Discusses the growing relevance of NARS, their technological, economic, and social drivers, and future challenges.

Unit 2: From Robots to Cobots

  • Section 1: Defines the distinction between machines and robots, exploring their evolution and characteristics.
  • Section 2: Delves into collaborative robots (cobots), their evolution, distinguishing features, and impact on workforce and productivity.
Part 1 - Unit 2 - From Robots to Cobots
Part 1 - Unit 3 - Components of Robots as a System

Unit 3: Components of Robots as a System

  • Section 1: Introduces gears in robotics, their role in force transmission, and practical applications.
  • Section 2: Examines common sensors in robotics, their classification, and functions.
  • Section 3: Discusses the concept and types of actuators in robotics and their real-life applications.
  • Section 4: Explores control systems in robotics, comparing manual and automatic systems.
  • Section 5: Details the integration process of sensors, actuators, and controllers in robotic systems.

Unit 4: Visualization, Design and Creation of Components

  • Section 1: Introduces the Quarky Ultimate Kit, its components, and programming features.
  • Section 2: Describes each part of the Quarky Robot and its programming logic.
  • Section 3: Highlights the features of TinkerCAD and provides tutorials for its use.
Part 1 - Unit 4 - Visualization, Design and Creation of Components
Part 1 - Unit 5 - Integrating Robots as a System

Unit 5: Integrating Robots as a System

  • Section 1 – 2 Wheel Drive Robot: Guides students in assembling and controlling a 2-wheel drive robot, including wireless operations and circular motion logic.
  • Section 2 – Line Follower Robot: Discusses the principles and programming logic behind line-following robots.
  • Section 3 – Obstacle Avoidance Robot: Focuses on assembling a robot capable of avoiding obstacles using ultrasonic sensors and relevant programming logic.
  • Section 4 – Edge Detection Robot: Teaches students to assemble and program a robot that can detect and react to edges to avoid falls.
  • Section 5 – Quarky Gripper Robot: Provides step-by-step instructions for assembling a robotic gripper, exploring its functionalities.
  • Section 6 – Pick and Place Robot: Covers the assembly and programming of a pick-and-place robot, demonstrating practical applications in automated systems.

Part 2: Artificial Intelligence Skills

This section covers decision-making in machines, machine vs human intelligence, cybersecurity, the AI project framework, and an introduction to data and programming with Python.

Part 2 - Unit 1 - Decision making in Machines and Computers

Unit 1: Decision Making in Machines / Computers

  • Section 1 – Automated versus Autonomous Systems: Explores the roles of automated and autonomous systems in technology, including deterministic and probabilistic systems.
  • Section 2 – Decision Making in Machines: Compares human and machine decision-making features, including object classification case studies.
  • Section 3 – Introduction to Machine Learning (ML): Covers machine learning basics, data’s role, and practical applications like fruit sorting in PictoBlox.

Unit 2: Machine Intelligence and Cybersecurity in Computing

  • Section 1 – Human and Machine Intelligence: Introduces machine intelligence, contrasting it with human intelligence.
  • Section 2 – The Turing Test: Discusses the significance, criteria, and implications of the Turing Test in AI development.
  • Section 3 – Connectivity Between Human and Machine Intelligence: Explores the collaborative potential, future prospects, and challenges in human-machine intelligence connectivity.
  • Section 4 – Cybersecurity: Addresses ethical and security issues in computing, cyber threats, countermeasures, and cybersecurity best practices.
Part 2 - Unit 2 - Machine Intelligence and Cybersecurity in Computing
Part 2 - Unit 3 - Components of AI Project Framework

Unit 3: Components of AI Project Framework

  • Section 1 – AI Project Cycle: Outlines the stages and processes in the AI project cycle.
  • Section 2 – Problem Scoping: Focuses on sustainable development goals, problem canvassing and statement formulation.
  • Section 3 – Data Acquisition: Discusses data sources, features, datasets, and acquisition strategies.
  • Section 4 – Data Exploration: Delves into methods and techniques for exploring and analysing data.
  • Section 5 – Modelling: Examines various modelling approaches including rule-based, supervised, and unsupervised learning.
  • Section 6 – Evaluation: Explores evaluation techniques and metrics for AI models.

Unit 4: Introduction to Data and Programming with Python

  • Section 1 – PictoBlox Python: Introduces PictoBlox Python Interface, offering an engaging platform for students to learn Python programming.
  • Section 2 – Recap of Python Programming: Covers the basics of Python, including syntax, data types, operators, and looping, with practical examples.
  • Section 3 – Python Packages: Teaches the installation and use of essential Python packages in PictoBlox, like NumPy, Matplotlib, Pandas, and SciPy.
  • Section 4 – Lists in Python: Explores the creation and manipulation of lists in Python, covering various methods and operations.
  • Section 5 – Tuples in Python: Discusses tuples in Python, including their creation, access methods, and conversion to and from lists.
  • Section 6 – String in Python: Delves into string manipulation in Python, including string traversal, concatenation, and slicing techniques.
Part 2 - Unit 4 Introduction to Data and Programming with Python

Part 3: Lab Activities on Python, Robotics, and Artificial Intelligence

This section of the book offers a series of lab activities encompassing advanced Python programming, robotics with Quarky, AI with PictoBlox, and machine learning applications.

Lab ActivityNameCategoryActivity Description
1Sorting a List of ClassmatesAdvance PythonCreate and sort a classmate name list in Python.
2Finding a Specific Word in a SentenceAdvance PythonDevelop a Python program to find a specific word in a sentence.
3Dictionary of Indian CitiesAdvance PythonCreate a Python dictionary with data about various Indian cities.
4 & 5Exploring NumPy Arrays – Part 1Advance PythonGain practical understanding of creating and manipulating NumPy arrays.
6Displaying an Image and Its NumPy Array RepresentationAdvance PythonDisplay an image and convert it into a NumPy array using Python libraries.
7Pandas Basics and Reading a CSV FileAdvance PythonLearn to read and manipulate data from a CSV file using Pandas.
8Reading JSON Data into a Pandas DataFrameAdvance PythonUnderstand how to read and analyze JSON data using Pandas.
9Basic Pandas OperationsAdvance PythonPractice basic data operations using Pandas in Python.
10Plotting X and Y Point Arrays using MatplotlibAdvance PythonPlot X and Y point arrays using the Matplotlib library.
11Plotting with Matplotlib - Markers, Line Styles, & Axis LabelsAdvance PythonExplore various plotting techniques using Matplotlib.
12Plotting Bar Graphs with Bestselling Book DataAdvance PythonUse Matplotlib to plot and analyze bestselling book data.
13Plotting Histograms with Top YouTubers' DataAdvance PythonCreate histograms to analyze data of top YouTubers.
14Regression - Predicting Future TemperaturesAdvance PythonPerform linear regression to predict future temperatures.
15Creating and Analysing a Normal DistributionAdvance PythonGenerate and analyze a set of scores following a normal distribution.
16Calculating Electricity BillAdvance PythonWrite a program to calculate electricity bills based on meter readings.
17Calculating Employee BonusAdvance PythonDevelop a Python program to calculate employee bonuses.
18LED Patterns with QuarkyRobotics with QuarkyControl Quarky's RGB LED grid to create gradient patterns.
19Creating a Touch Piano with QuarkyRobotics with QuarkyTransform Quarky into a touch-sensitive piano using Python.
20Programming the Quarky Robot's MovementsRobotics with QuarkyProgram Quarky to move in different directions.
21Wirelessly Controlled RobotRobotics with QuarkyLearn to control Quarky's movements using keyboard keys.
22 & 23Calibrating and Programming a Line-Following RobotRobotics with QuarkyProgram and calibrate a line follower robot with Quarky.
24Programming Quarky Obstacle Avoidance RobotRobotics with QuarkyProgram an obstacle avoidance robot using Quarky and Python.
25Programming Quarky for Edge AvoidanceRobotics with QuarkyProgram a robot for edge avoidance using ultrasonic sensors.
26Programming Quarky Gripper RobotRobotics with QuarkyProgram a Quarky robot to perform pick and place actions.
27Programming Pick and Place RobotRobotics with QuarkyProgram a Quarky Pick and Place robot for specific actions.
28Face Detection with PythonAI with PictoBloxLearn face detection basics using Python in PictoBlox.
29Finger Tracking with PythonAI with PictoBloxUnderstand hand detection for tracking fingers using Python.
30 & 31Mask Detection with Image Classifier (ML)ML with PictoBloxCreate a mask detection system with PictoBlox's ML environment.
32 & 33Fruit Detection with Image Classifier (ML)ML with PictoBloxDevelop a fruit classifier system using PictoBlox's ML tools.
34NLP Based Text ClassifierML with PictoBloxImplement a text classifier for basic NLP applications in PictoBlox.
35, 36 & 37Gesture-Controlled Beetle in the Maze GameML with PictoBloxCreate a gesture-controlled game using a trained ML model.
38 & 39Yoga Pose Detector with Pose ClassifierML with PictoBloxDevelop a Yoga Pose Detection system using PictoBlox's ML tools.
40Self-Driving Car with QuarkyAI and RoboticsProgram a simulated self-driving car that responds to traffic signs.

Part D - Project Work / Field Visit / Student Portfolio

This section focuses on project-based learning, encouraging students to apply their knowledge in real-world scenarios. It includes a Capstone Project – Codeavour, a showcase of sample projects from the community, and answer keys for self-evaluation.

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FAQs on Robotics and AI - Class 10 Book (Subject Code 66)

This book aims to comprehensively introduce Class 10 students to the fundamentals and advanced concepts of Robotics and AI. It is designed to foster a deep understanding of these fields, equipping students with practical skills through hands-on activities and projects. The curriculum is developed to help students navigate and contribute to the evolving landscape of technology, thereby preparing them for future technological challenges and career opportunities.

This book, specifically designed for Class 10 students, is fully aligned with the ICSE Subject Code 66, focusing on Robotics and Artificial Intelligence (AI). Its unique approach and features are as follows:

  1. Curriculum Alignment: It meticulously covers all essential topics outlined in the ICSE Robotics and AI curriculum, ensuring a comprehensive grasp of both theoretical and practical aspects.
  2. Interactive Learning Tools: The book incorporates PictoBlox and Quarky for practical learning. PictoBlox simplifies AI concepts through interactive activities, while Quarky offers hands-on robotics experience.
  3. Comprehensive Coverage: Divided into four parts, it covers Robotics, AI, lab activities, and project work. Each section is detailed, providing depth and breadth in learning.
  4. Activity-Based Learning: Emphasizes practical activities and lab exercises, fostering an engaging and interactive learning environment.
  5. Expert Authorship: Written by experts in technology and AI, the book offers authoritative and practical knowledge.
  6. Modern Technological Content: Tailored to match the technological interests of today’s students, it includes updated content on current trends and advancements.
  7. Ethical AI Understanding: Discusses the ethical aspects and responsibilities associated with AI technology, preparing students for responsible future technology use.
  8. Resource for Teachers and Students: Includes an answer key for exercises, numerous lab activities, and assignments, aiding in tracking learning progress and self-assessment.
  9. Future-Ready Skills: The book prepares students for future technological landscapes by fostering AI-readiness, developing problem-solving skills, and enhancing critical thinking through practical applications.

This book stands out for its comprehensive, interactive, and practical approach to teaching Robotics and AI, aligning with the ICSE curriculum and catering to the educational needs of Class 10 students.

The book is authored by Pankaj Kumar Verma, Chief Technology Officer at STEMpedia, an alumnus of IIT Kanpur, and Khushbu Chauhan, an AI & Robotics Expert at STEMpedia, with a BE degree from Gujarat Technological University. Their expertise ensures the content is both educational and technically accurate.

The book stands out for its comprehensive coverage of Robotics and AI, combined with engaging practical activities. It includes modern technological content tailored to match the interests of today’s students. The book emphasises activity-based learning to foster interactive understanding of concepts. Detailed step-by-step guidance ensures students can easily grasp complex topics. Additionally, the book contains challenging exercises including multiple-choice questions, short answers, and higher-order thinking questions to test and enhance understanding.

The book is divided into four main parts:

  • Part 1 focuses on Robotics, exploring the evolution, applications, and practical aspects of robotic systems.
  • Part 2 delves into Artificial Intelligence, covering decision-making in machines, machine vs. human intelligence, cybersecurity, and Python programming.
  • Part 3 comprises Lab Activities on Python, Robotics, and AI, offering hands-on experience.
  • Part 4 includes Project Work and Miscellaneous resources, such as a capstone project and sample community projects.

The curriculum aims to develop a foundational understanding of Robotics and AI among students. It focuses on building expertise through a blend of theory and practical work, enhancing appreciation and understanding of these subjects. The course prepares students for future technological advancements by introducing key AI concepts and computational skills, including Python programming. It also raises awareness about the ethical implications of AI technologies.

Absolutely. The book aligns with the ICSE Robotics and AI curriculum (Subject Code 66) for Class 10. It covers all the essential topics and skills required for the exams, making it a valuable resource for students preparing for their final assessments.

  • PictoBlox: PictoBlox is an intuitive and engaging Python platform that simplifies complex AI concepts for students. It uses interactive activities such as image classification, object detection, and natural language processing to make learning AI accessible and enjoyable.
  • Quarky: Quarky is a robotic tool that offers students a hands-on experience in robotics. It allows students to explore robotic movements, sensor usage, and control systems in a practical setting, thus deepening their understanding of robotics.

The book offers extensive coverage of Python programming, starting from the basics and advancing to more complex concepts and libraries relevant to AI and robotics. It includes practical examples and exercises to ensure students understand the application of Python in the field of AI and robotics.

The book supports practical learning in robotics through detailed lab activities and project work. Students get to assemble and program various types of robots, applying their theoretical knowledge in a hands-on environment. These activities are designed to enhance their understanding of robotic systems and their components, along with programming skills.

Yes, the book includes a comprehensive answer key for exercises and detailed guidance for project work. This support ensures students can effectively learn from their mistakes and gain a deeper understanding of the subject matter.

While the book is designed with classroom instruction in mind, its clear structure and comprehensive content also make it suitable for self-study. Students who are motivated and disciplined can use this book to learn independently.