Robotics

Indian Institute of Technology Madras

Students graduating with a dual degree in Robotics shall be capable of understanding and analyzing the following:

Basic robotic technologies used across various applications
Kinematics, dynamics, and control of Industrial and field/service robots
Sensing, perception, planning, and control applied to autonomous robots
Application of Artificial Intelligence, Neural Networks and Reinforcement learning in Robotics
Hardware systems and controllers used in robotics
Design of robotic systems for new applications

Program Offers

The ID-DD programme is offered by faculty from the departments of Aerospace Engineering, Applied Mechanics, Civil Engineering, Computer Science and Engineering, Electrical Engineering, Engineering Design, Mechanical Engineering and Ocean Engineering. The true interdisciplinary nature of Robotics is reflected in the joint programme collectively offered by faculty from various Depts.

Enrollment

A B. Tech student or a Dual Degree student of IIT Madras in any discipline (except biosciences) is eligible to upgrade/opt for this programme provided the student has a CGPA of 8.0 or above up to 5th semester. Total number of seats will be fixed at 25 and allocation of dual degree specialization and award of the degree will be governed by the rules of the Institute.

Curriculum

ID-DD-Robotics has a very flexible curriculum. The programme spans a period of five semesters of the five-year dual degree programme. There will be a bridge course covering the basics of electrical, mechanical, and computer science fundamentals applicable to robotics. This course will ensure that the students who enters into this specialisation from different streams have the basic understanding of robotics. The curriculum also allows short term (1-3 months)/ long term (up to 6 months) internships with potential companies / research organizations.

In tune with the overall structure of the dual degree program being offered in the Institute, the number of courses to be offered and the credit distribution are as follows:

Total Credits required

150 to 160

No. of PMT CORE courses to be offered

3 (33 credits)

No. of electives to be offered

4 ( 36±2 credits)

No. of labs. to be offered

1 ( 6 credits)

Project work/internship

1 (85 credits)

Interdisciplinary DD in Robotics -course curriculum

Sl.No	Course No	Course Name	L	T	E	P	O	C
	Semester 6
1	ID6040	Core 1: Introduction to Robotics	4	0	0	0	8	12
		Total credits						12
	Semester 7
1	ED6007	Core 2: Mechanics and Control of Serial Manipulators	4	0	0	0	8	12
		Electives
		Total Credits :						12
	Semester 8
1	ID5690	Internship/Summer Project (Project I)						20
		Electives
	Semester 9
1	ED5315	Core 3: Field and Service Robotics	3	0	0	0	6	9
2	ID6100	Core Lab1: Robotics Laboratory	0	0	0	3	3	6
	ID5691	Project II						25
		Total Credits :						15
	Semester 10
1	ID 5692	Project III						40
		Total Credits :

Project

85 credits to be completed in 8th, 9th and 10th semester

Electives

36±2 credits to be completed from the approved list in 7th, 8th, and 9th semester

Total credits for the DD programme

160

ELECTIVE COURSES

Electives will be offered in three baskets. Students need to choose the electives from at least two baskets (no student will be allowed to choose all the electives from one basket). Faculty/Dept. consent has been received for all the electives.

Sl.No	Course No	Course Name	L	T	E	P	O	C
		Basket 1
1	AS5012	Dynamics and control of rotorcraft	3	0	0	0	6	9
2	AS5040	Flight Mechanics	4	0	0	0	8	12
3	AS 5010	Aerodynamics and Aircraft Performance	3	0	0	0	6	9
4	AS5340	Advanced flight mechanics	3	0	0	0	6	9
5	AM5010	Biomechanics	3	0	0	0	6	9
6	AM5190	Haptics in Biomedical Engg	3	0	0	0	6	9
7	AM5011	Virtual Reality Engg.	3	0	0	0	6	9
8	ED5314	Design, analysis and control of Robot Manipulators	3	0	0	0	6	9
9	OE 5011	Marine Robotics	3	0	0	0	6	9
10	ME7010	Microprocessor in automation	3	0	0	0	6	9
11	CE6011	Smart buildings and automation	3	0	0	0	6	9
12	ED5040	Human Anatomy Physiology and Biomechanics	4	0	0	0	8	12
13	ED5160	Automotive systems	4	0	0	0	88	12
14	OE5310	Guidance & Control of Marine Vehicles	3	0	0	0	6	9
15	ME6221	Theory of Mechanisms	3	0	0	0	6	9
16	AS5570	Principles of Guidance for Autonomous Vehicles	3	0	0	0	6	9
17	AS5545	Dynamics and Control of Spacecraft
		Basket 2
1	CS5011/ EE5177	Machine Learning for Computer Vision	4	0	0	0	8	12
2	CS6380	Artificial intelligence	4	0	0	0	8	12
3	CS6700	Reinforcement learning	4	0	0	0	8	12
4	CS7015	Deep Learning	4	0	0	0	8	12
5	CS6350/ EE5175	Computer Vision/ Image Signal Processing	4	0	0	0	8	12
6	CS6777	Optimisation for computer vision applications	4	0	0	0	8	12
7	ID5030	Machine Learning for Engineering and Science Applications	3	1	0	0	6	10
8	CS5691	Pattern Recognition and Machine Learning
9	CS6910	Fundamentals of Deep Learning
		Basket 3
1	EE5541	Synthesis of control systems	3	0	0	0	6	9
2	EE6417	Allied topics in control systems	3	0	0	0	6	9
3	EE6412	Optimal Control	4	0	0	0	8	12
4	EE5340	Micro-electro mechanical systems	3	0	0	0	6	9
5	EE5410	Introduction to DSP	4	0	0	0	8	12
6	EE5177/ CS5011	Machine Learning for Computer Vision	4	0	0	0	8	12
7	EE5175/ CS6350	Image Signal Processing	4	0	0	0	8	12
8	EE6415	Nonlinear Control Systems	3	0	0	0	6	9
9	ED5330	Control of Automotive Systems