A Human-Centered Dynamic Scheduling Architecture for Collaborative Application
This addresses scheduling challenges for human-robot teams in collaborative settings, but it appears incremental as it builds on existing dynamic scheduling concepts.
The paper tackles dynamic task scheduling in human-robot collaborative applications by proposing a two-layered architecture that considers job quality and real-time human activity monitoring, with experimental validation showing effectiveness.
In collaborative robotic applications, human and robot have to work together during a whole shift for executing a sequence of jobs. The performance of the human robot team can be enhanced by scheduling the right tasks to the human and the robot. The scheduling should consider the task execution constraints, the variability in the task execution by the human, and the job quality of the human. Therefore, it is necessary to dynamically schedule the assigned tasks. In this paper, we propose a two-layered architecture for task allocation and scheduling in a collaborative cell. Job quality is explicitly considered during the allocation of the tasks and over a sequence of jobs. The tasks are dynamically scheduled based on the real time monitoring of the human's activities. The effectiveness of the proposed architecture is experimentally validated.