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Towards safe robot-human collaboration systems using human pose detection

机译:迈向使用人体姿态检测的安全的机器人与人的协作系统

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摘要

This paper proposes a human detection-based cognitive system for robots to work in human-existing environment and keep the safety of humans. An integrated system is implemented with perception, recognition, reasoning, decision-making, and action. Without using any traditional safety cages, a vision-based detection system is implemented for robots to monitor the environment and to detect humans. Subsequently, reasoning and decision making enables robots to evaluate the current safety-related situation for humans and provide corresponding safety signals. The decision making is based on maximizing the productivity of the robot in the manipulation process and keep the safety of humans in the environment. The system is implemented with a Baxter humanoid robot and a PowerBot mobile robot. Practical experiments and simulation experiments are carried out to validate our design.
机译:本文提出了一种基于人类检测的认知系统,用于机器人在人类存在的环境中工作并保持人类安全。通过感知,识别,推理,决策和行动来实现一个集成系统。在不使用任何传统安全笼的情况下,为机器人实现了基于视觉的检测系统来监视环境并检测人员。随后,推理和决策使机器人能够为人类评估当前与安全有关的情况并提供相应的安全信号。决策的依据是在操纵过程中最大限度地提高机器人的生产率,并确保环境中人员的安全。该系统由Baxter人形机器人和PowerBot移动机器人实现。进行了实践实验和仿真实验以验证我们的设计。

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