Shankar, S. B. (2025). Development of the MRVR Robotic Dummy User: An Omnidirectional Robot Emulating Human Movements in an Interactive VR Environment [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2025.133182
E193 - Institut für Visual Computing and Human-Centered Technology
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Date (published):
2025
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Number of Pages:
91
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Keywords:
Virtual Reality; Robotics
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Abstract:
The emergence of collaborative robotic systems has led to increasingly close interactionsbetween robots and human operators, raising concerns about safety—especially withinsystems like interactive virtual reality (VR) environments where physical boundariesare less perceptible. The ability of collaborative systems to interact closely and safelywith humans is a critical factor in their advancement. Therefore, establishing effectivedevelopment methodologies that ensure safety and enable reliable testing is essential fortheir successful deployment. This study aims to develop a platform for the safe and reliable testing of collaborative mobile robotic systems that must dynamically adjust theirposition based on their proximity to human collaborators to ensure safe interaction. Specifically, the study focuses on developing a robotic system capable of reliably replicatingcomplex human trajectories using holonomic mobile robots, thereby providing a safe andcontrolled platform for repeated testing. The study explores a foundational approachesto achieve the desired trajectory emulation using Robot Operating System and its navigation Stack. The method’s practical limitations, particularly in accurately replicatingtime-sensitive trajectories with the holonomic robot and providing easy configuration fordiverse motion patterns is discussed. Recognizing and learning from these limitations,the study progresses to develop a refined trajectory emulation framework composed ofcustom ROS-compatible modules designed to closely replicate human trajectories withhigh fidelity. Comprehensive evaluations conducted in both simulated and real-worldenvironments demonstrate the effectiveness and robustness of the proposed framework.In simulation, the system achieved a mean positional error on the order of 1 × 10−5 m,with latency consistently maintained below 100ms. In real-world tests, the frameworkmaintained a mean positional error in the order of 1 × 10−3 m, also with latency below100ms. These results validate the system’s performance while also highlighting areas forpotential improvement in real-world deployment conditions. The current study providesa solid foundation for the development of a safe and reliable testing platform, facilitatingthe advancement of intelligent and collaborative robotic systems.
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