MR4018 Mobile Robotics Syllabus:

MR4018 Mobile Robotics Syllabus – Anna University PG Syllabus Regulation 2021

COURSE OBJECTIVES

1. To introduce mobile robotic technology and its types in detail.
2. To learn the kinematics of wheeled and legged robot.
3. To familiarize the intelligence into the mobile robots using various sensors.
4. To acquaint the localization strategies and mapping technique for mobile robot.
5. To aware the collaborative mobile robotics in task planning, navigation and intelligence.

UNIT – I INTRODUCTION TO MOBILE ROBOTICS

Introduction – Locomotion of the Robots – Key Issues on Locomotion – Legged Mobile Roots – Configurations and Stability – Wheeled Mobile Robots – Design Space and Mobility Issues – Unmanned Aerial and Underwater Vehicles – Teleportation and Control.

UNIT – II KINEMATICS

Kinematic Models – Representation of Robot – Forward Kinematics – Wheel and Robot Constraints – Degree of Mobility and Steerability – Mano euvrability – Workspace – Degrees of Freedom – Path and Trajectory Considerations – Motion Controls – Holonomic Robots – Open Loop and Feedback Motion Control – Humanoid Robot – Kinematics Overview.

UNIT – III PERCEPTION

Sensor for Mobile Robots – Classification and Performance Characterization – Wheel/Motor Sensors – Heading Sensors – Ground-Based Beacons – Active Ranging – Motion/Speed Sensors – Vision Based Sensors – Uncertainty – Statistical Representation – Error Propagation – Feature Extraction Based on Range Data (Laser, Ultrasonic, Vision-Based Ranging) – Visual Appearance based Feature Extraction.

UNIT – IV LOCALIZATION

The Challenge of Localization – Sensor Noise and Aliasing – Effector Noise – Localization Based Navigation Versus Programmed Solutions – Belief Representation – Single – Hypothesis Belief And Multiple-Hypothesis Belief – Map Representation – Continuous Representations – Decomposition Strategies – Current Challenges In Map Representation – Probabilistic Map Based Localization – Markov Localization – Kalman Filter Localization – Landmark-Based Navigation – Globally Unique Localization – Positioning Beacon Systems – Route-Based Localization – Autonomous Map Building – Stochastic Map Technique – Other Mapping Techniques.

UNIT – V PLANNING, NAVIGATION AND COLLABORATIVE ROBOTS

Introduction – Competences for Navigation: Planning and Reacting – Path Planning – Obstacle Avoidance – Navigation Architectures – Modularity for Code Reuse and Sharing – Control Localization – Techniques for Decomposition – Case Studies – Collaborative Robots – Swarm Robots.

TOTAL: 45 PERIODS

COURSE OUTCOMES:

Upon completion of this course, the students will be able to:
CO1: Evaluate the appropriate mobile robots for the desired application.
CO2: Create the kinematics for given wheeled and legged robot.
CO3: Analyse the sensors for the intelligence of mobile robotics.
CO4: Create the localization strategies and mapping technique for mobile robot.
CO5: Create the collaborative mobile robotics for planning, navigation and intelligence for desired applications.

REFERENCES:

1. Dragomir N. Nenchev, Atsushi Konno, Teppei Tsujita, “Humanoid Robots: Modelling and Control”, Butterworth-Heinemann, 2018
2. Mohanta Jagadish Chandra, “Introduction to Mobile Robots Navigation”, LAP Lambert Academic Publishing, 2015.
3. Peter Corke, “Robotics, Vision and Control”, Springer, 2017.
4. Roland Siegwart and Illah R.Nourbakish, “Introduction to Autonomous Mobile Robots” MIT Press, Cambridge, 2004.
5. Ulrich Nehmzow, “Mobile Robotics: A Practical Introduction”, Springer, 2003.
6. Xiao Qi Chen, Y.Q. Chen and J.G. Chase, “Mobile Robots – State of the Art in Land, Sea, Air, and Collaborative Missions”, Intec Press, 2009.