Course

Introduction to UAV – Types of UAV – Geometry and Mechanics of UAVs including transformations, angular velocity, principal moment of inertia, equations of motions, ROS based Control, Trajectories and Motion Planning, Sensing and Probabilistic State Estimation, Visual Motion Estimation, Visual SLAM, Architectures, UAV and AGV interoperable frameworks.

Learning Objectives

LO1: To understand the fundamentals, classification, and applications of UAV systems.

LO2: To explore the mechanics, dynamics, and mathematical modelling of UAV motion.

LO3: To learn ROS-based control strategies, motion planning, and trajectory generation.

LO4: To understand state estimation and visual navigation techniques (e.g., SLAM, VIO).

Course Outcomes

CO1: Classify UAVs and explain their functional and structural components.

CO2: Analyze the geometry, dynamics, and kinematics of UAVs including inertial
          modelling.

CO3: Design and simulate motion planning and control algorithms using ROS-based
          frameworks.

CO4: Apply sensing techniques and probabilistic filters for UAV state estimation.

CO5: Evaluate and implement visual SLAM and motion estimation algorithms for UAV
          navigation.

CO-PO Mapping

Textbooks/References:

1. Thrun, Sebastian, Wolfram Burgard, and Dieter Fox. Probabilistic Robotics. MIT press, 2005.
2. Carrillo, Luis Rodolfo García, et al. Quad rotorcraft control: vision-based hovering and Springer Science & Business Media, 2012.
3. Corke, Robotics, vision and control: fundamental algorithms in MATLAB® second, completely revised. Vol. 118. Springer, 2017.