Michele Polito

Papers

Total Citations

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About

Michele Polito is a robotics researcher whose work lies at the intersection of human-robot collaboration, exoskeleton design, and real-time perception systems. His research focuses on making robots more responsive and safer partners for humans, particularly through the integration of deep learning and novel sensor technologies. Polito’s most cited work introduces a deep learning technique that identifies abrupt human movements during collaborative tasks, a critical step toward preventing injuries and improving trust in shared workspaces. He has also contributed to the experimental characterization of active joints for trunk exoskeletons, advancing wearable assistive devices that support industrial workers and rehabilitation patients. More recently, his demonstration of real-time event camera communication with collaborative robots showcases a cutting-edge approach to high-speed, low-latency robot control. Though early in his career, Polito’s publications—garnering citations from 2022 to 2024—signal a growing impact in the fields of physical human-robot interaction and intelligent manufacturing. His work exemplifies the practical engineering required to bridge the gap between theoretical robotics and real-world applications, making him a promising voice in the next generation of collaborative robotics research.