Shenbagaraj Kannapiran

Papers

Total Citations

H-Index

About

Shenbagaraj Kannapiran is a robotics researcher whose work bridges the gap between scaled-down autonomous systems and full-size vehicle intelligence. His most impactful contribution is the **Go-CHART**, a miniature 1:28 scale self-driving car robot (20 citations), which replicates the sensing and computational capabilities of a full-size autonomous vehicle in a compact, four-wheel skid-steer platform. This accessible platform enables rapid prototyping and testing of autonomous driving algorithms without the cost and risk of full-scale trials. Kannapiran has also advanced the field of **visual-inertial odometry (VIO)** with his 2021 framework that integrates 3D points, lines, and planes for robust camera pose estimation—a critical component for 3D reconstruction and SLAM in texture-poor environments. His work addresses fundamental challenges in feature correspondence under difficult visual conditions. By combining practical robotic design with sophisticated perception algorithms, Kannapiran contributes to making autonomous navigation research more accessible and reliable, with his Go-CHART platform serving as a valuable educational and experimental tool for students and researchers alike.