Shubham Paliwal

Indian Institute of Information Technology Allahabad

Papers

Total Citations

H-Index

About

Shubham Paliwal is a robotics researcher whose work bridges the gap between classical motion planning and cutting-edge artificial intelligence. His primary research areas include path planning algorithms for service robotics and the integration of large language models (LLMs) into robotic process automation (RPA). Paliwal’s most notable contribution is the "Maximum clearance rapid motion planning algorithm" (2018), which addresses critical limitations in traditional bug-family algorithms by improving cost-efficiency, security, and robustness for real-world service robot navigation. This work has earned 8 citations and remains a reference point for researchers tackling complex, cluttered environments. More recently, Paliwal introduced "SmartFlow: Robotic Process Automation using LLMs" (2024), a pioneering framework that replaces rigid pixel-level encoding with LLM-driven decision-making, enabling RPA systems to handle diverse screen layouts and intricate workflows with human-like adaptability. Although newly published with 2 citations, SmartFlow signals a transformative shift toward cognitive automation. Paliwal’s dual focus on foundational algorithms and AI-augmented systems demonstrates a rare ability to advance both theoretical and applied robotics, making his work essential reading for students and researchers interested in the future of autonomous systems.