Enhancing Performance in Human–Robot Collaboration: A Modular Architecture for Task Scheduling and Safe Trajectory Planning

摘要

The integration of robots into shared workspaces alongside humans is the basis of Human-Robot Collaboration (HRC). This field of research has changed the paradigm of the industrial context, making HRC of pivotal importance for both researchers and the industry. In this context, a suitable task scheduling and trajectory planning strategy are crucial to achieve good performances and create a synergy between the two actors. Indeed, the task scheduling should be able to optimally distribute the tasks between the actors and recover from possible failures, i.e. by rescheduling the tasks. The trajectory planning strategy must comply with the safety standards that impose a reduction of velocity based on human behaviour. To this end, the monitoring system must also be safe-certified; otherwise, safety cannot be guaranteed. This paper proposes a novel architecture that integrates a dynamic task scheduling module with a dynamic trajectory planning module that explicitly considers ISO/TS 15066. For this purpose, the framework exploits a secure and certified monitoring system capable of tracking the human operator even in case of occlusions. The overall platform has been extensively validated both in a real and complex industrial scenario within the context of the ROSSINI EU project, where a dual-arm mobile robot collaborates with a human operator in an automatic machine-tending operation, and in a mock-up scenario.