Towards Safe, Realistic Testbed for Robotic Systems with Human Interaction

IEEE International Conference on Robotics and Automation(2022)

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摘要
Simulation has been a necessary, safe testbed for robotics systems (RS). However, testing in simulation alone is not enough for robotic systems operating in close proximity, or interacting directly with, humans, because simulated humans are very limited. Furthermore, testing with real humans can be unsafe and costly. As recent advances in machine learning are being brought to physical robotic systems, how to collect data as well as evaluate them with human interactions safely yet realistically is a critical question. This paper presents a Mixed-Reality (MR) system toward human-centered development of robotic systems emphasizing benefits as a data collection and testbed tool. MR testbeds allow humans to interact with various levels of virtuality to maintain both realism and safety. We detail the advantages and limitations of these different levels of realism or virtualization, and report our MR-based RS testbed implemented using off-the-shelf MR devices with the Unity game engine and ROS. We demonstrate our testbed in a multi-robot, multi-person tracking and monitoring application. We share our vision and insights earned during the development and data collection.
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关键词
data collection,testbed tool,RS testbed,multirobot,realistic testbed,human interaction,necessary testbed,safe testbed,robotics systems,simulated humans,physical robotic systems,Mixed-Reality system,human-centered development
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