CP4091 Autonomous Systems Syllabus:
CP4091 Autonomous Systems Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
To impart knowledge on the functional architecture of autonomous vehicles
To impart knowledge on Localization and mapping fundamentals
To impart knowledge on process end effectors and robotic controls
To learn Robot cell design, Robot Transformation and Sensors
To learn Micro/Nano Robotic Systems
UNIT I INTRODUCTION AND FUNCTIONAL ARCHITECTURE
Functional architecture – Major functions in an autonomous vehicle system, Motion Modeling – Coordinate frames and transforms, point mass model, Vehicle modeling (kinematic and dynamic bicycle model – two-track models), Sensor Modeling – encoders, inertial sensors, GPS.
UNIT II PERCEPTION FOR AUTONOMOUS SYSTEMS
SLAM – Localization and mapping fundamentals, LIDAR and visual SLAM, Navigation – Global path planning, Local path planning, Vehicle control – Control structures, PID control, Linear quadratic regulator, Sample controllers.
UNIT III ROBOTICS INTRODUCTION, END EFFECTORS AND CONTROL
Robot anatomy-Definition, law of robotics, Simple problems Specifications of Robot-Speed of Robot-Robot joints and links-Robot classifications-Architecture of robotic systems, Mechanical grippers-Slider crank mechanism, Screw type, Rotary actuators, cam type-Magnetic grippers Vacuum grippers-Air operated grippers-Gripper force analysis-Gripper design-Simple problems Robot controls-Point to point control, Continuous path control, Intelligent robot Control system for robot joint-Control actions-Feedback devices-Encoder, Resolver, LVDT Motion Interpolations Adaptive control.
UNIT IV ROBOT TRANSFORMATIONS, SENSORS AND ROBOT CELL DESIGN
Robot kinematics-Types- 2D, 3D Transformation-Scaling, Rotation, Translation- Homogeneous coordinates, multiple transformation-Simple problems. Sensors in robot – Touch sensors-Tactile, Robot work cell design and control-Sequence control, Operator interface, Safety monitoring devices in Robot-Mobile robot working principle, actuation using MATLAB, NXT Software.
UNIT V MICRO/NANO ROBOTICS SYSTEM
Micro/Nano robotics system overview-Scaling effect-Top down and bottom up approach Actuators of Micro/Nano robotics system-Nano robot communication techniques-Fabrication of micro/nano grippers-Wall climbing micro robot working principles-Biomimetic robot-Swarm robot-Nano robot in targeted drug delivery system.
COURSE OUTCOMES:
CO1: Understand architecture and modeling of autonomous systems.
CO2: Employ localization mapping techniques for autonomous systems
CO3: Design solutions for autonomous systems control.
CO4: Analyze Robot Transformations, Sensors and Cell Design
CO5: Explain the working principles of Micro/Nano Robotic system
TOTAL: 45 PERIODS
REFERENCES
1. S.R. Deb, Robotics Technology and flexible automation, Tata McGraw-Hill Education.,2009
2. Mikell P Groover & Nicholas G Odrey, Mitchel Weiss, Roger N Nagel, Ashish Dutta, Industrial Robotics, Technology programming and Applications, McGraw Hill, 2012.
3. Karsten Berns, Ewald Puttkamer, Springer, Autonomous Land Vehicles: Steps towards Service Robots, 2009
4. Sebastian Thrun, Wolfram Burgard, Dieter Fox., Probabilistic robotics. MIT Press, 2005
5. Steven M. LaValle., Planning algorithms, Cambridge University Press, 2006
6. Daniel Watzenig and Martin Horn (Eds.), Automated Driving: Safer and More Efficient Future Driving, Springer, 2017
7. Markus Maurer, Autonomous driving: technical, legal and social aspects. Springer, 2016
8. Jha, Theory, Design and Applications of Unmanned Aerial Vehicles, CRC Press, 2016