IIT Madras Offers Free Online Course on Robotics for Students; Certificate Available
IIT Madras Offers Free Online Course on Robotics for Students; Certificate Available
Indian Institute of Technology Madras Internship
Indian Institute of Technology (IIT) Madras is offering a free online course on robotics for undergraduate and graduate students.Indian Institute of Technology (IIT) Madras has invited applications from students for a free online course on Robotics. This course can be completed in 12 weeks.
Things to know:
- The course aims at providing an understanding of mechanical, electrical, and computer science aspects of robotics.
- This course is a bridge-course for undergraduate or graduate students from various disciplines to get a basic understanding of robotics.
- The course will be conducted by Dr T Asokan who is a professor in the department of engineering design, and currently the head of the department, Prof Balaraman Ravindran who is currently a professor in computer science, and Dr Krishna Vasudevan who is a professor in the department of electrical engineering at IIT Madras.
- While the course is free to enroll, if you want a certificate, you have to register and write the exam conducted in person at any of the designated exam centers.
- The exam is optional for a fee of Rs 1000/-
- Certificates will be rewarded based on the participant’s performance in the exam, as well as their average assignment score.
- The average assignment score will be 25 per cent of average of best eight assignments out of the total 12 assignments given in the course, and exam score consists of 75 per cent of the proctored certification exam score out of 100.
What will you learn?
IIT Madras free online course
Apply for this course now!
Week 1: Introduction to robotics- History, growth; Robot applications- Manufacturing industry, defense, rehabilitation, medical etc., Laws of Robotics
Week 2: Robot mechanisms; Kinematics- coordinate transformations, DH parameters
Week 3: Forward kinematics, Inverse Kinematics
Week 4: Jacobians, Statics, Trajectory Planning
Week 5: Actuators (electrical)- DC motors, BLDC servo motors
Week 6: Sensors, sensor integration
Week 7: Control – PWM, joint motion control, feedback control
Week 8: Computed torque control
Week 9: Perception, Localisation and mapping
Week 10: Probabilistic robotics, Path planning, BFS; DFS; Dijkstra; A-star; D-star; Voronoi; Potential Field; Hybrid approaches
Week 11: Simultaneous Localization and Mapping
Week 12: Introduction to Reinforcement Learning
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