Collaborative Robots with Cognitive Capabilities for Industry 4.0 and Beyond
Open accessAbstract
The robots that entered the manufacturing sector in the second and third Industrial Revolutions (IR2 and IR3) were designed for carrying out predefined routines without physical interaction with humans. In contrast, IR4* robots (i.e., robots since IR4 and beyond) are supposed to interact with humans in a cooperative way for enhancing flexibility, autonomy, and adaptability, thus dramatically improving productivity. However, human–robot cooperation implies cognitive capabilities that the cooperative robots (CoBots) in the market do not have. The common wisdom is that such a cognitive lack can be filled in a straightforward way by integrating well-established ICT technologies with new AI technologies. This short paper expresses the view that this approach is not promising and suggests a different one based on artificial cognition rather than artificial intelligence, founded on concepts of embodied cognition, developmental robotics, and social robotics. We suggest giving these IR4* robots designed according to such principles the name CoCoBots. The paper also addresses the ethical problems that can be raised in cases of critical emergencies. In normal operating conditions, CoCoBots and human partners, starting from individual evaluations, will routinely develop joint decisions on the course of action to be taken through mutual understanding and explanation. In case a joint decision cannot be reached and/or in the limited case that an emergency is detected and declared by top sec…
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Hybrid AI methods integrating fuzzy logic, neural networks, and reinforcement learning with a three-layer fusion model improve efficiency in multi-agent human-robot collaboration with moderate overhead.
“Hybrid Artificial Intelligence (AI) methods integrate fuzzy logic, neural networks, and RL with a three-layer fusion model, improving efficiency in multi-agent HRC [8,41], with moderate overhead [42].”
From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [42]
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Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability
Urrea, C. (2025) · Actuators · doi:10.3390/act14040177 · Cited by 19 · see citing works
“…94% accuracy [11] High GPU needs [27] Reinforcement Learning 90% recovery [28], 98% resilience [17] Safety risks [13] Hybrid AI 95% efficiency [41], 98% resilience [8] 20–30% overhead [42] Hybrid redundancy combines mechanical and algorithmic strengths, balancing robustness and adaptability.”
- Authors
- Sandini, G., Sciutti, A., & Morasso, P.
- Affiliations
- Italian Institute of Technology (IT)
- Corresponding author
- Morasso, Pietro
- Venue
- AI
- Publisher
- MDPI AG
- Published
- 2024-10-09
- Volume
- 5
- Issue
- 4
- Pages
- 1858-1869
- ISSN
- 2673-2688 (ISSN-L)
- OpenAlex
- W4403303190
- Cited by
- 7
- References
- 5
- Citations by year
- 2026: 2 · 2025: 5
- FWCI
- 1.10
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- AI (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Fondazione Istituto Italiano di Tecnologia, RBCS Department, in relation with the iCog Initiative (804388)
- European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (804388)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Engineering › Control and Systems Engineering › Robotics and Automated Systems
- Keywords
- collaborative robots, human-robot collaboration, Industry 4.0, artificial cognition, embodied cognition, developmental robotics, social robotics, shared decision-making, human-robot interaction, manufacturing automation
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