Ai in Robotics detailed Syllabus for Automation & Robotics (AO), K scheme PDF has been taken from the MSBTE official website and presented for the diploma students. For Subject Code, Subject Name, Lectures, Tutorial, Practical/Drawing, Credits, Theory (Max & Min) Marks, Practical (Max & Min) Marks, Total Marks, and other information, do visit full semester subjects post given below.
For all other MSBTE Automation & Robotics 4th Sem K Scheme Syllabus PDF, do visit MSBTE Automation & Robotics 4th Sem K Scheme Syllabus PDF Subjects. The detailed Syllabus for ai in robotics is as follows.
Rationale
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Course Outcomes:
Students will be able to achieve & demonstrate the following COs on completion of course based learning
- Determine initial state and goal state for a given problem.
- Use relevant AI search strategies for problem solving.
- Interpret different types of knowledge and reasoning techniques used in AI.
- Apply the learning methods adopted in AI.
- Apply the principles of AI in robotics.
Unit I
Basics of Artificial Intelligence 1.1 AI: Definition and characteristics, history, scope, need for AI in Robotics 1.2 Agent and environment: Definition, characteristics and classification of agents, rational agent and intelligent agent, environment and its properties 1.3 State space search: Goal directed agent, State space search notations-Initial state, action or an operator, plan, path cost 1.4 AI Ethics: Transparency, fairness, accountability, privacy, security
Lecture usin chalk and bo Presentation
Unit II
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Unit III
Knowledge, Reasoning and Planning 3.1 Knowledge: Definition and types of knowledge 3.2 Knowledge representation techniques, AI knowledge life cycle 3.3 Knowledge based agent in AI: Introduction, architecture, rules of inference, first order logic, forward chaining and backward chaining 3.4 Reasoning: Definition and its types, forward reasoning and backward reasoning, probabilistic reasoning: need, cause of uncertainty, bayesian reasoning 3.5 Planning: Definition, types of planning, planning graph
Lecture usin chalk and bo Presentation Demonstrati
Unit IV
Learning adopted in AI 4.1 Forms of learning, knowledge in learning, statistical learning methods, Importance of AI in learning 4.2 Machine learning: Definition, techniques in machine learning – supervised learning, unsupervised learning, reinforcement learning, semi-supervised learning 4.3 Introduction to predictive modeling: definition, stages of predictive modeling – problem definition, hypothesis generation, data extraction/collection, data exploration and transformation, splitting dataset into training set and test set, types of predictive models, algorithms of predictive modelling 4.4 Communication, perceiving and acting, probabilistic language processing and perception
Lecture usin chalk and bo Presentation Demonstrati Flipped Classroom
Unit V
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List of Experiments:
- * Identification of initial state and goal state for a given 3-pegs problem 2 C
- Identification of initial state and goal state for a given problem on chessboard 2 C
- * Implementation of breadth first search algorithm 2 C
- Implementation of depth first search algorithm 2 C
- * Implementation of forward chaining algorithm 2 C
- Implementation of travelling salesman problem 2 C
- * Implementation of forward chaining algorithm 2 C
- Implementation of backward chaining algorithm 2 C
- Implementation of forward reasoning 2 C
- * Implementation of backward reasoning 2 C
- Implementation of Bayesian reasoning 2 C
- Implementation of data extraction 2 C
- * Develop a program to split dataset 2 C
- * Implementation of motion commands for robot using simulator 2 C
- Implementation of end effector command for a given robot 2 C
- Execution of robotic operations by bridging robotvision systems 2 C
- * Implementation of specific path movement of robot 2 C
- Implementation of painting operation with AI based robot 2 C
Self Learning
Micro Project
- Case study on various future applications of robotic systems.
- Case study on future AI based technology.
- Case study on robotics system used in the automobile / manufacturing industry.
Student Activity
- Prepare a power point presentation on the topic Future of AI in robotics.
- Prepare a chart on various types of search algorithms.
Laboratory Equipment
For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
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Learning Materials
- Russell, S.; Norvig, P. Artificial Intelligence: A Modern Approach Publicher: Pearson ISBN : 9780134610993
- Poole, David L.; Mackworth, Alan K. Artificial Intelligence: Foundations of Computational Agents Publisher: Cambrid University Press ISBN : 9781107195394
- Nilsson, Nils J. The Quest for Artificial Intelligence Publisher: Cambrid University Press ISBN : 9780521116398
- Knight, Kevin; Rich, Elaine; Nair, Shivashankar B. Artificial Intelligence Publisher: McGraw Education ISBN : 9780070087705
- Jones, M. Tim Artificial Intelligence: A Systems Approach Publisher: Jones an Bartlett Learning ISBN : 9780763773373
- Govers, Francis X. Artificial Intelligence for Robotics: Build intelligent robots that perform human tasks using AI techniques Publisher: Packt Publishing Limited ISBN : 9781788835442
- Deb, S. R.; Deb, Sankha Robotics Technology and Flexible Automation Publisher: McGraw Education ISBN : 9780070077911
- Chowdhary, K. Fundamentals of artificial Intelligence Publisher: Springer India Private Ltd. ISBN : 9788132239703
- Murphy, Robin R. Introduction to AI Robotics Publisher: The MIT Press ISBN : 9780262038485
- Jefferis, David Artificial Intelligence: Robotics and Machine Evolution Publisher: Crabtree Publishing Compa ISBN : 9780778700463
Learning Websites
- https://www.javatpoint.com/artificial-intelligence-ai Artificial Intelligence
- https://www.simplilearn.com/tutorials/artificial-intelligenc e-tutorial Artificial Intelligence
- https://www.tutorialspoint.com/artificial_intelligence/index .htm Artificial Intelligence
- https://techvidvan.com/tutorials/robotics-and-artificial-int elligence/ Robotics and AI
- https://www.bertelkamp.com/media/documents/training/RT_Toolb ox3_Details.pdf?_cchid=39fca59addcd41d2401d433a3c68eaf8 Simulation S/W RT Toolbox3
- https://www.allied-automation.com/rt-toolbox3-robot-simulati on/ Simulation S/W RT Toolbox3
- https://nptel.ac.in/courses/106/105/106105078/ NPTEL Web Content- Artificial Intelligence, Prof. P. Mitra, Prof. S Sarkar, IIT Kharagpur
- https://onlinecourses.nptel.ac.in/noc23_ge40/preview SWAYAM course- Fundamental of By Prof. Shyamanta M. Hazarika , Guwahati
- https://www.javatpoint.com/search-algorithms-in-ai Artificial Intelligence
- http://www.roboanalyzer.com/uploads/2/5/8/8/2588919/roboanal yzerusermanual.pdf Roboanalyzer user manual
- https://cse22-iiith.vlabs.ac.in/exp/self-organizing-maps/ Virtual lab
For detail Syllabus of all other subjects of Automation & Robotics, K scheme do visit Automation & Robotics 4th Sem Syllabus for K scheme.
For all Automation & Robotics results, visit MSBTE Automation & Robotics all semester results direct links.