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About

David Corinaldi is a researcher whose work sits at the intersection of parallel robotics, optimal motion planning, and sustainable automation. His primary contributions lie in the kinematic and dynamic optimization of spherical parallel manipulators (SPMs) for high-speed, dexterous pointing tasks. Corinaldi’s research is distinguished by its focus on exploiting functional redundancy—the ability of a robot to perform a task in multiple ways—to enhance performance. His most cited work, "Singularity-free path-planning of dexterous pointing tasks for a class of spherical parallel mechanisms" (26 citations), provides a foundational method for avoiding singularities, a critical challenge in parallel robotics. He further advanced the field by developing dynamic optimization strategies that minimize inertial loads during fast pointing motions, as detailed in his 2018 letter (17 citations) and related work on posture optimization (12 citations). Beyond traditional robotics, Corinaldi has explored the feasibility of automated disassembly for electronic waste recycling (11 citations), demonstrating the practical application of robotic cells for end-of-life component recovery. His work on reconfigurable parallel platforms, such as the novel 3-URU design, showcases his interest in versatile, multi-modal robotic systems. With a cumulative citation count exceeding 80, Corinaldi is recognized for bridging theoretical kinematics with real-world, high-performance robotic applications.