Mehul Arora

University of Bonn, Indian Institute of Information Technology Allahabad

Papers

Total Citations

H-Index

About

Mehul Arora is a robotics researcher specializing in autonomous navigation, 3D perception, and semantic mapping. His work focuses on enabling robots to build accurate, long-term environmental representations using cost-effective sensors. Arora’s most cited paper, “Static map generation from 3D LiDAR point clouds exploiting ground segmentation” (2022, 29 citations), introduces a method to filter dynamic objects from LiDAR data, producing clean, static maps critical for reliable robot localization. He also tackles a fundamental challenge in visual SLAM—continuous drift in budget-grade camera systems—through his work on “SLAM and Map Learning using Hybrid Semantic Graph Optimization” (2022). This approach integrates semantic understanding into graph-based SLAM to reduce drift without relying on rare loop closures, making everyday navigation more robust. By combining geometric and semantic cues, Arora’s contributions advance practical, low-cost autonomous systems for real-world deployment. His research is particularly impactful for field robotics, where sensor constraints and dynamic environments are the norm.