D. Dupuis

University of British Columbia, Queen's University

Papers

Total Citations

H-Index

About

D. Dupuis is a roboticist whose work bridges motion planning and intelligent systems, with a focus on vision-guided manipulation and autonomous gameplay. His major contributions lie in two key areas: occlusion-aware path planning and the development of competitive robotic pool players. In his 2008 paper on occlusion-free path planning, Dupuis introduced a novel algorithm that uses a probabilistic roadmap to compute collision-free trajectories for articulated robot arms equipped with “eye-in-hand” sensors, ensuring continuous visual tracking of targets—a critical advance for inspection and assembly tasks. This work has garnered 17 citations, reflecting its utility in sensor-based robotics. Dupuis is perhaps best known for his role in creating Deep Green, a vision-based robotic system designed to play pool at a better-than-amateur level. His 2008 paper on the system, also with 17 citations, details how computer vision and robotic control enable the robot to plan shots and execute precise strikes, with the ultimate goal of challenging a proficient human opponent. A related 2007 paper explores the role of computational intelligence in such gameplay. Together, these works showcase Dupuis’s ability to integrate perception, planning, and control into a cohesive, competitive system, making him a notable figure in applied robotics.