Intelligent Field Robotics Lab


The intelligent field robotics lab aims to expand the knowledge in the areas of robotics design, architecture, and modelling, robotics vision, and perception, unmanned aerial vehicle (VAU), intelligent autonomous robots, swarm robotics, human-robot interaction, robots imitation learning, self-supervised learning, and medical assistive robotics. The main objective of this lab is to provide a conducive applied research environment for the development of advanced robotic systems. 

Field robots are an essential and integral part of the modern industrial revolution. These robots handle the tasks autonomously, intelligently, and precisely. The use of robots in smart agriculture for pesticide spraying, irrigation, disaster management, and monitoring, smart city for safety, and such is the research of the day. 

The intelligent field robotics laboratory covers a wide range of technology to create future robotics, from human-friendly robots used in super-aging society and self-controlled smart mechanical systems to intelligent spaces and smart society as extended robotics concepts. Research projects will include various topics such as the coordinated control systems of multiple robots, self-controlled robots, intelligent welfare machines, sensors based on micro-electromechanical systems technology, sensor networks, and nano-robots.

Aims & Objectives

  1. Study the Incorporating of artificial intelligence into machines so that they can deal with real-world situations. 
  2. Research to design groups of robots that operate without relying on any external infrastructure or on any form of centralized control. 
  3. Study of human-robot interaction is a multidisciplinary field with contributions from human-computer interaction, artificial intelligence, robotics, natural language understanding, design, and psychology. 
  4. Research autonomous vehicles, driverless cars, or robo-car, a vehicle capable of sensing its environment and moving safely with little or no human input. 
  5. Researching and developing systems that can learn for themselves and be able to operate in the home, the workplace, and even on the sports field. 

Research Areas

  • Self-Supervised learning 
  • Imitation Learning 
  • Reinforcement Learning 
  • Computer Vision for Autonomous Robots 
  • Autonomous Vehicles 
  • Robots’ Communication Networks 
  • Swarm Robotics 
  • AI-based Medical Assistance 
  • Human-Robot Interaction 
  • Agricultural Robotics 
  • Smart Autonomous Robots 
  • Intelligent Agent and Multiagent Systems 
  • Autonomous Mobile Robots 
  • Wireless Collaborative Robotics 
  • Intention Understanding in Human-Robot 
  • Miniature Robotics 
  • Aerial Robots and Unmanned Aerial Vehicles (UAV) 


  • Autonomous guided vehicle 
  • Mobile Robots 
  • Autonomous Ground Robot 
  • Robot Arm Kit 
  • Macanum Wheels Robot Kit 
  • Arduino and Raspberry Pi Kits 
  • Robotics Car 
  • Spider Bot Kit 
  • High-Performance Computing (HPC) cluster  
  • HPC workstation 


Sound-based accident detection in autonomous vehicle

Communication Protocols in swarm robotics network

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