Robot Motion Planning

Course Syllabus

Name of the Course: Robot Motion Planning
LTP structure of the course: 2-1-1
Objective of the course: The course enables the students learn the basics of mobile robotics and helps them understand the mechanisms to plan and navigate different types of robots from a pre-specified source to a pre-specified goal using a variety of Artificial Intelligence techniques.
Outcome of the course: From this course the students will be able to appreciate intelligent robotic systems involving single and multiple robots, get a good grasp in Artificial Intelligence tools and techniques from an application point of view, and be able to plan for different robots in different conditions and constraints.
Course Plan: As per the below format only

Component	Unit	Topics for Coverage (Theory)	Topics for Coverage (Practice)	Chapter No.(Optional)
Component 1	Unit 1	Introduction, Configuration Spaces, Collision Detection, Bug Algorithms	Simple collision-checking for different types of robots in 2D workspaces	1, 2, 3
Component 1	Unit 2	A* Algorithm and Roadmap Based Approach	Constructing 2D configuration spaces	5, H
Component 2	Unit 3	Sampling based Robotics, Cell-Decomposition approaches	OMPL installation and play-through	6, 7
Component 2	Unit 4	Optimization based planning, Hybrid Planning, Multi-Robot Motion Planning	Writing planners using OMPL	Selected research papers by the instructor

Text Book:
- H. Choset, K. M. Lynch, S. Hutchinson, G. A. Kantor, W. Burgard, L. E. Kavraki, S. Thrun (2005) Principles of Robot Motion: Theory, Algorithms, and Implementations, MIT Press, Cambridge, MA.
References:
- S. M. LaValle (2006) Planning Algorithms, Cambridge University Press, NY.
- R. Kala (2016) On-Road Intelligent Vehicles: Motion Planning for Intelligent Transportation Systems, Elsevier, Waltham, MA