Stephan Schweizer

Papers

Total Citations

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About

Stephan Schweizer is a researcher focused on advancing human-robot interaction, particularly through augmented reality (AR) and flexible team coordination. His work bridges the gap between intuitive robot control and autonomous collaboration, with a key contribution being the development of a smart-device-based AR robot operation interface using Google Tango technology. This system, detailed in his 2018 paper (11 citations), enables operators to program and control robots remotely via a Java application, leveraging self-tracking and depth-sensing capabilities for enhanced spatial awareness. Schweizer also explores dynamic task allocation in human-robot teams, as seen in his 2019 work (4 citations), where he introduces skill interaction categories to manage communication when abstract task models fall short. His research addresses critical challenges in making robot interfaces more accessible and teamwork more fluid, with potential applications in manufacturing and service robotics. By combining AR with task-level coordination, Schweizer contributes to a future where humans and robots collaborate seamlessly, offering practical solutions for real-world deployment.