Khalid Mahmood Arif

About

Khalid Mahmood Arif is a multidisciplinary robotics and artificial intelligence researcher whose work spans agricultural automation, mobile robotics, indoor localization, and robotic manipulation. He has made particularly significant contributions to the application of machine and deep learning in agriculture, with his 2021 review on automation in agriculture accumulating over 400 citations — a testament to the field's hunger for comprehensive, accessible syntheses of emerging AI-driven farming technologies. Arif's robotics research demonstrates a consistent drive to solve real-world challenges using cost-effective, practical solutions. His pioneering work on visible light communication (VLC) for indoor robot localization brought theoretical simulation concepts into tangible experimental implementation, while subsequent hybrid positioning systems further refined this approach. His investigations into floor surface profiling using low-cost sensors reflect a commitment to democratizing advanced robotic sensing capabilities for everyday industrial applications. In the domain of robotic manipulation, Arif has developed innovative machine learning-based methodologies for autonomous object grasping — tackling one of robotics' most persistently difficult challenges. His additional contributions to 3D biopolymer printing using robotic assistance highlight remarkable breadth. Collectively, his work bridges intelligent systems, computer vision, and practical robotics, making him a valuable voice for researchers and students navigating the intersection of AI and autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Automation in Agriculture by Machine and Deep Learning Techniques: A Review of Recent Developments

   404 citations · 2021
2. 2
   Robot-assisted 3D printing of biopolymer thin shells

   49 citations · 2016
3. 3
   Indoor localization of mobile robot with visible light communication

   48 citations · 2016
4. 4
   Robot-Assisted Floor Surface Profiling Using Low-Cost Sensors

   8 citations · 2019
5. 5
   A 3-Stage Machine Learning-Based Novel Object Grasping Methodology

   8 citations · 2020
6. 6
   HVLP: Hybrid visible light positioning of a mobile robot

   6 citations · 2017
7. 7
   Floor surface mapping using mobile robot and 2D laser scanner

   5 citations · 2017
8. 8
   Towards the autonomous robotic gripping and handling of novel objects

   4 citations · 2019
9. 9
   Towards the autonomous robotic gripping and handling of novel objects

   3 citations · 2019
10. 10
    A Benchmarking Platform for Learning-Based Grasp Synthesis Methodologies

    3 citations · 2021

Key Collaborators

Contact & Links