Who we are ?

We are a bunch of overly optimistic, hardworking students working towards creating I.I.T. Kanpur's first Autonomous Under Water Vehicle. The current team consists of 20 students spanning various branches of engineering like Mechanical, Electrical, Computer Science, Physics, Material Science and Chemical at Indian Institute of Technology Kanpur.
Our mission is to participate in AUV competitions like NIOT SAVe, Robosub. The competition is a platform for students to display their skills in underwater robotics and build a connection with industries working along similar verticals.
Our vision is to lower the entry barier for research in underwater robotics. For this we have designed Varun such that any of its mechanical, electrical or software component can be individually improved and tested. Thus enabling researchers to focus on there field of research and using other pre-baked components.


Sub Teams

  • Electrical

    The electrical team ensures efficient power management and a smooth interface between the processor and the actuators & sensors.

  • Mechanical

    The mechanical team is responsible for designing, prototyping and manufacturing of complete vehicle consisting of frame, waterproof hull, torpedoes etc.

  • Software

    The software team is responsible for programing the robot to complete tasks autonomously using data from sensors and controlling motion using actuators.

AUV Competitions


ESSO-National Institute of Technology (NIOT) , under the Ministry of Earth Sciences, is organize a competition for students pursuing engineering degree to visualize and design an autonomous underwater vehicle.The conceptual basis for Student Autonomous underwater Vehicle (SAVe), is a highly mobile Autonomous Underwater Vehicle (AUV) to be built based on engineering principles. The main focus of this competition is to involve students on the new frontier areas of ocean technology and kindle their innovative thinking in this unexplored area of ocean environment and observation. NIOT will support the winning team with their technical expertise and also sponsor for the International competition being held annually in AUVSI foundation San Diego, USA.The competition is open to Indian national students only. Read more...

Robo Sub

Student-designed-and-built autonomous robotic submarines must complete a difficult series of visual- and acoustic-based tasks in this popular international competition. These tasks simulate the work required of robotic subs in many facets of underwater activity. Read more...


Held since 2006, SAUC-E challenges the next generation of engineers to design and build an autonomous underwater vehicle (AUV) capable of performing realistic missions. The event is designed to encourage students to think about underwater technology and related applications while fostering innovation and technology. It also aims at getting young engineers and scientists to consider careers in the field. Participating teams must consist of 75% student members and have a faculty advisor. Read more...

Singapore AUV Challenge

The Singapore AUV challenge aims to provide students an opportunity to experience the challenges of AUV system engineering and develop skills in the associated technologies. The focus is on autonomous operations in a swimming pool format, rather than remote control in a small tank, and it is aimed at University and Polytechnic students. The Singapore AUV challenge emphasizes on outreach, learning and skill development. The competition is open to Singapore and international participants. Read more...

Research Collaborations

Research on Path Planning Techniques

Given information of a target and obstacles we are trying to implement various path planning algorithms like grid-based navigation, A star algorithm, potential path planning for AUV and compare there efficiency under water. This project is in collaboration with Lokesh Singh, who is a Research Assistant at IIT Kanpur and hold expertise in the field of robotic path planning.

Inverse Kinematics using Machine Learning

Path planning gives us the trajectory of the most efficient path but to move on that path we have to fire up our actuators and accelerate in the right direction. This is done by Inverse Kinematics ie. mapping displacement to actuator voltages. AUV team in collaboration with Mtech. student Hitesh Jangid is trying to implement machine learning algorithms like SVM for automatically callibrating these mappings.