It is widely agreed that future manufacturing environments will be populated by humans and robots sharing the same workspace. However, the real collaboration can be sporadic, especially in case of assembly tasks which might involve autonomous operations to be executed by either the robot or the human worker. In this scenario, it might be beneficial to predict the actions of the human in order to control the robot both safely and efficiently. In this paper, we propose a method to predict human activity patterns in order to early infer when a specific collaborative operation will be requested by the human and to allow the robot to perform alternative autonomous tasks in the meanwhile. The prediction algorithm is based on higher-order Markov Chains and is experimentally verified in a realistic scenario involving a dual-arm robot employed in a small part collaborative assembly task.
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