Design of a Human-Centric Collaborative Robotic Workstation using Multimodal Sensing for Speed and Separation Monitoring

Collaborative robots support flexible, human-centric manufacturing, but raise concerns about physical and cognitive safety due to the removal of traditional safety physical barriers. This research work presents the design of a collaborative robotic workstation in which Speed and Separation Monitoring (SSM), as defined in ISO 10218-2:2025 – Robotics — Safety requirements addresses physical safety, while a novel Human-Machine Interface (HMI) is introduced to reduce cognitive overload and improve user awareness and trust. A multimodal sensing system combining 2D LiDAR and RGB-D is used for human detection. Decision-making is controlled by a Behaviour Tree (BT), enabling intelligent responses based on safety state. The system was developed using the V-Model design methodology, ensuring rigorous testing and safety integration from early stages. Implementation within the ROS2 framework enables modularity and future scalability. Testing confirmed safe operation, and participant feedback validated the system’s effectiveness and trustworthiness. This work has led to an innovative approach that combines multimodal sensing and real-time intelligent decision-making, built into a ROS2-based digital twin, to achieve a safe and collaborative robotic experience.