Garrit Strenge

Papers

Total Citations

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About

Garrit Strenge is a researcher at the forefront of human-robot interaction, specializing in the development of seamless, intuitive object handovers between humans and robots. His work focuses on replicating the natural, anticipatory movements of human-human handovers—characterized by early motion onset and smooth velocity profiles—to create more fluid and efficient robotic systems. Strenge's key contributions include leveraging Gaussian processes to predict human trajectories, enabling robots to anticipate handover locations and coordinate their movements accordingly. He has also developed models that utilize submovements—a fundamental feature of human motion—for enhanced trajectory planning and prediction. To ensure practical applicability, Strenge has proposed a real-time object localization method using low-cost RGB cameras, making his research accessible for real-world deployment. With his most-cited papers accumulating citations in 2023 alone, Strenge is establishing himself as a rising expert in the field. His work not only advances the technical capabilities of collaborative robots but also deepens our understanding of how to emulate human inference and coordination in physical human-robot interaction.