Rahul Shivaji Pol

About

Rahul Shivaji Pol is a robotics and autonomous systems researcher whose work centers on mobile robot navigation, path planning algorithms, and intelligent robotic control systems. His most influential contribution, a comprehensive 2015 survey on indoor autonomous mobile robot navigation through dynamic environments, has garnered 51 citations and remains a foundational reference for researchers tackling real-world path planning challenges — including multi-room layouts, hallways, and environments dense with static and dynamic obstacles. Pol has consistently advanced this domain, developing the Realistic and Optimal Path Planning Algorithm (ROPPA) in 2020, which enhances system performance through socio-realistic navigation frameworks, and extending this work into grid-based trajectory planning methodologies in 2021. Beyond navigation, his 2016 research on a LabVIEW-controlled four degrees-of-freedom robotic ARM demonstrated his practical engineering acumen, delivering an organized and cost-effective robotic control solution. Across his body of work, Pol bridges theoretical algorithm design with real-world implementation, making his research particularly valuable for engineers and students working on applied autonomous robotics. With over 84 cumulative citations, his contributions continue to inform advances in intelligent mobile systems and human-aware robotic environments.

Research Focus

Key Achievements

Top Papers

1. 1
   A review on indoor human aware autonomous mobile robot navigation through a dynamic environment survey of different path planning algorithm and methods

   51 citations · 2015
2. 2
   LabVIEW based four DoF robotic ARM

   14 citations · 2016
3. 3
   Socio-realistic optimal path planning for indoor real-time autonomous mobile robot navigation

   13 citations · 2020
4. 4
   Grid Based Realistic Optimal Path Planning

   6 citations · 2021

Key Collaborators

Contact & Links