Gajanan Kanagalingam

University of Kaiserslautern, University of Stuttgart

Papers

Total Citations

H-Index

About

Gajanan Kanagalingam is a robotics researcher focused on advancing the autonomy, precision, and safety of industrial and collaborative robotic systems. His work centers on real-time motion control, collision and deadlock avoidance, and path optimization for multi-robot environments. Kanagalingam’s most cited paper, “Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators” (2022, 24 citations), introduces a nonlinear model predictive control algorithm that enables multiple manipulators to operate safely and efficiently in dynamic settings—a critical contribution for flexible manufacturing. He also addresses the precision limitations of lower-cost robots in “Increasing Robot Precision by Stroke Division” (2023), proposing a method to enhance repeatability for tasks like welding and painting. In “Quasi Time-Optimal Path Tracking for Pneumatic Robots” (2024), he tackles the unique challenges of pneumatic direct-drive robots, balancing speed and safety by incorporating third-order actuator constraints. His research bridges theoretical control methods with practical industrial applications, offering scalable solutions for collaborative robotics. With growing citation impact and a focus on real-world deployment, Kanagalingam is establishing himself as a promising voice in intelligent robotic manipulation.