Robotics and Automation in Agriculture

Visual perception for robotic systems in agricultural environments

This project was conducted at IIT Kanpur, India, under the Ministry of Electronics and Information Technology (MeitY), Government of India.
The goal was to develop robotic perception systems for agricultural automation, enabling robots to operate reliably in unstructured farm environments.

My role focused on visual perception for robotic systems, including scene understanding and object detection required for autonomous agricultural tasks.

Project Overview

Agriculture presents challenging perception conditions such as cluttered scenes, varying lighting conditions, and occlusions from foliage.
This project investigated how computer vision and machine learning methods can improve perception for robotic manipulation and navigation in farms.

Key objectives included:

  • Developing robust vision-based perception pipelines
  • Improving object detection and segmentation in agricultural environments
  • Supporting robotic decision-making through visual scene understanding

Research Contributions

  • Designed visual perception modules for robotic agricultural systems
  • Developed approaches for scene understanding in cluttered environments
  • Contributed to improving robot autonomy through visual sensing

Project Details

Institution: IIT Kanpur, India
Position: Senior Student Research Associate
Duration: Apr 2022; Sep–Nov 2022; Jan–Apr 2023
Funding Agency: Ministry of Electronics and Information Technology (MeitY), Government of India