Thomas Galluzzo

Carnegie Mellon University, University of Florida

Papers

Total Citations

154

H-Index

About

Thomas Galluzzo is a robotics researcher whose work bridges perception, planning, and control to create truly autonomous manipulation systems. His most influential contribution, "An integrated system for autonomous robotics manipulation" (2012, 120 citations), introduced a groundbreaking software architecture that tightly integrates perception, planning, and control, enabling robots to autonomously grasp and dexterously manipulate objects with minimal human oversight. This foundational work has become a key reference in the field. Galluzzo further advanced robotic autonomy with his development of a real-time, markerless arm tracking method using stochastic gradient descent (2018, 27 citations), which robustly corrects kinematic errors from depth sensor data—a practical solution for closed-loop servoing. His earlier research established core principles in mobile robot navigation, including receding horizon control techniques for autonomous ground vehicles operating in cluttered environments. Galluzzo’s career demonstrates a consistent focus on moving robots from structured labs to real-world applications, making him a notable figure in autonomous robotics.