Manufacturing industries are eager to replace traditional robot manipulators with collaborative robots due to their cost-effectiveness, safety, smaller footprint and intuitive user interfaces. With industrial advancement, cobots are required to be more independent and intelligent to do more complex tasks in collaboration with humans. Therefore, to effectively detect the presence of humans/obstacles in the surroundings, cobots must use different sensing modalities, both internal and external. This paper presents a detailed review of sensor technologies used for detecting a human operator in the robotic manipulator environment. An overview of different sensors installed locations, the manipulator details and the main algorithms used to detect the human in the cobot workspace are presented. We summarize existing literature in three categories related to the environment for evaluating sensor performance: entirely simulated, partially simulated and hardware implementation focusing on the ‘hardware implementation’ category where the data and experimental environment are physical rather than virtual. We present how the sensor systems have been used in various use cases and scenarios to aid human–robot collaboration and discuss challenges for future work.

由于协作机器人具有成本效益、安全性、占地面积更小和直观的用户界面，制造业迫切希望用协作机器人取代传统的机器人操纵器。随着工业的进步，协作机器人需要更加独立和智能，以与人类协作完成更复杂的任务。因此，为了有效地检测周围环境中人类/障碍物的存在，协作机器人必须使用不同的内部和外部传感方式。本文详细回顾了用于在机器人操纵器环境中检测人类操作员的传感器技术。概述了不同传感器的安装位置、机械手的详细信息以及用于在协作机器人工作空间中检测人体的主要算法。我们将现有文献总结为与评估传感器性能的环境相关的三个类别：完全模拟、部分模拟和硬件实现，重点是“硬件实现”类别，其中数据和实验环境是物理的而不是虚拟的。我们介绍了如何在各种用例和场景中使用传感器系统来帮助人机协作并讨论未来工作的挑战。