Help by Predicting What to Do

Alati, Edoardo; Mauro, Lorenzo; Ntouskos, Valsamis; Pirri, Fiora

doi:10.1109/icip.2019.8803155

Cited by 3 publications

(1 citation statement)

References 20 publications

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“…However, the order in which such atomic tasks are performed by the operator to conclude the cycle, in general, is not uniquely defined. Therefore, for a machine to be aware of the current state of an assembly cycle, it is required to recognize any atomic task executed by the operator and to model the transitions between them (Alati et al 2019b). Identifying a task implies understanding the actions being performed by the operator, while understanding the transitions between tasks implies predicting the operator's intentions.…”

Section: Human-robot Cooperation In Assemblymentioning

confidence: 99%

AI and ML for Human-Robot Cooperation in Intelligent and Flexible Manufacturing

Garcia

Rauch

Vidoni

et al. 2021

Implementing Industry 4.0 in SMEs

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Human–robot cooperation aims to increase the flexibilization of manufacturing systems. This requires safe human–machine interaction (e.g. with collaborative robots) as well as self and environment awareness capabilities to interact autonomously and smartly between humans and machines. Therefore, the goal of this chapter is to conceptualize and identify the set of real-time information processing and decision-making capabilities required for collaborative robots to be considered as a safe companion in the context of human–robot cooperation (HRC). In particular, the chapter provides an overview of appropriate artificial intelligence (AI) and machine learning (ML) concepts, formally introduces the concept of a safety-aware cyber-physical system and defines a general taxonomy for the perceptive and cognitive problems arising in the context of intelligent and flexible HRC.

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Section: Human-robot Cooperation In Assemblymentioning

confidence: 99%