AGV

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Autonomous Ground Vehicle
Founded 2011 (2011)
Founder(s) Dibyendu Ghosh, Nalin Gupta, Srinivas Reddy
Website agv-iit-kgp.github.io


AGV (Autonomous Ground Vehicle) is a research group under Prof. Debashish Chakravarty, Mining department, aiming to create a self-driving car.

AGV participates in Intelligent Ground Vehicle Competition (IGVC) every year. This year they are also participating in Mahindra Rise Prize Driverless Car Challenge. The team in divided in embedded electronics, software and mechanical parts.

Vision[edit | edit source]

"Our vision is to have the world without road accidents; a place where people can commute without fear, to build the world’s most advanced and cost effective self-driving car."

  • The present transportation system is getting increasingly expensive and inefficient.
  • Over $230 billion are spent on car crashes every year, a majority of which are due to human errors.
  • Congestion in total amounts to 10.5 billion litres of wasted petrol each year.
  • Over 4.2 billion hours are wasted in traffic every year.
  • There has been an increase in the number of accidents due to human errors such as drinking and driving.

The solution to all these problems is a self-­driving car. With this inspiration, we have started Autonomous Ground Vehicle (AGV) Research Group in IIT Kharagpur. We aspire to make India’s first fully operational self-driving car.

Goals[edit | edit source]

Mahindra Rise Prize[edit | edit source]

India has been on the verge of greatness for too long. It's time to change that. It’s time to make the world sit up and take notice. To create disruptive solutions that transform lives. To lead in enterprise and innovation. To see "Made in India" mean best in the world. This is Mahindra Rise Prize challenge aims at. We at AGV have been selected in the first round of this challenge and we are looking forward to applying our technology to a Mahindra Vehicle making it fully Autonomous.

Intelligent Ground Vehicle Challenge[edit | edit source]

The IGVC offers a design experience that is at the very cutting edge of engineering education. It is multidisciplinary, theory-based, hands-on, team implemented, outcome assessed, and based on product realisation. It encompasses the very latest technologies impacting industrial development and taps subjects of high interest to students. Design and construction of an Intelligent Vehicle fit well in a two-semester senior year design capstone course, or an extracurricular activity earning design credit. The deadline for an end-of-term competition is a real-world constraint that includes the excitement of potential winning recognition and financial gain. Students solicit and interact with industrial sponsors who provide component hardware and advice, and in that way get an inside view of industrial design and opportunities for employment. Team AGV has been constantly participating in Intelligent Ground Vehicle Competition and making a mark.

Research Applications[edit | edit source]

Mine Mapping[edit | edit source]

The lack of accurate maps of underground mines frequently causes mine accidents. Hazardous operating conditions and difficulty in access makes Robotic Exploration and Mapping an immediate and safe choice.The mapping algorithms used in the self-driving car can also be applied for mines.

Construction Mapping[edit | edit source]

Large-scale construction projects might involve exploration of areas inaccessible or life­ threatening to workers. For such scenarios, a portable mapping solution could be hosted on a small flying quadrotor.

City Mapping[edit | edit source]

The traditional surveying techniques for generating maps for city­ planning requires thousands of man-hours and are very expensive. Large cities can be mapped accurately and efficiently using a self-driving car equipped with 3­D laser mapping technologies. This can cut down on a lot of manual work and save time. With this view, we undertook the DIGITAL KGP PROJECT in which we mapped some parts of the IIT Kharagpur campus using the 3­D ENVIRONMENT MAPPING Technology.

Night Time Driver Assist[edit | edit source]

The use of special sensors in autonomous driving systems can detect approaching vehicles and road boundaries under poor lighting conditions. This feature could be widely used in vehicles as an essential safety measure.

Lane Departure Warning System[edit | edit source]

This system warns the driver as soon as the vehicle starts moving out of the lane. If the driver, for some reason, avoids the warning, the system takes over and moves the vehicle back into the lane. This technology completely removes the human error involved in the process.

Collision Detection System[edit | edit source]

A sensing system has a wider field of view compared to an average human being. It is also capable of running calculations at over 2.5 GHz. Owing to these qualities, a sensing system can warn the driver beforehand about a probable collision.

References[edit | edit source]

AGV IIT Kharagpur