Justin Stoecker

Papers

Total Citations

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About

Justin Stoecker’s research sits at the intersection of robotics, motion planning, and interactive visualization, with a focus on enabling more robust and intuitive control for simulated and real-world robotic systems. His most-cited work, “Motion Capture and Contemporary Optimization Algorithms for Robust and Stable Motions on Simulated Biped Robots” (2013, 5 citations), pioneers the integration of motion capture data with modern optimization techniques to generate stable, human-like locomotion for bipedal robots—a foundational challenge in legged robotics. Stoecker also developed an innovative tool for “Interactive visualization of 3D configuration spaces” (2013, 2 citations), which allows users to explore the contact surfaces of planar robots navigating static obstacles through both 2D and 3D views. This work advances the understanding of configuration space geometry, making complex spatial reasoning more accessible for robot path planning. Though his citation counts are modest, Stoecker’s contributions are notable for their practical approach to bridging simulation and real-world motion, and his visualization tool remains a valuable resource for students and researchers seeking to demystify robot-environment interactions.