David Littau

University of Minnesota, Centre for Artificial Intelligence and Robotics, Twin Cities Orthopedics

Papers

Total Citations

H-Index

About

David Littau’s research centers on vision-based robotic control, particularly the challenge of enabling robots to interact with real-world objects using limited visual feedback. His major contribution lies in pioneering shape morphing and image morphing techniques for eye-in-hand robotic systems—where a single camera is mounted on the robot’s end-effector. Rather than relying on complex calibration or pre-programmed models, Littau’s work demonstrated how virtual images could guide a robot to grasp diverse objects by dynamically aligning its pose with the target. This fundamentally new approach to visual servoing reduces the need for exhaustive object recognition and trajectory planning. Though his most-cited papers—such as “Grasping real objects using virtual images” (4 citations) and “Pose alignment of an eye-in-hand system using image morphing” (2 citations)—have modest citation counts, they represent early, inventive steps in adaptive robotic manipulation. Littau’s research laid groundwork for more flexible, vision-driven robotic systems, influencing later advances in autonomous grasping and real-time visual control.