# Mind, Machine, and Meaning: Cognitive Ergonomics and Adaptive Interfaces in the Age of Industry 5.0
## 3 Ergonomic Techniques in Human-Machine Interactions
### Modern Solutions for Improving Human-Machine Interactions
#### 3.3.2 Collaborative Robots and Human Assistance in Industry 5.0  
Collaborative robots (cobots) represent one of the most impactful technologies in modern manufacturing, as they enhance productivity, safety, and flexibility by working directly alongside humans. These systems are central to the emerging concept of Industry 5.0, which emphasizes not just automation and efficiency but also sustainability, resilience, and human-centric values [104]. Whereas Industry 4.0 emphasized the automation and the integration of cyber-physical systems, Industry 5.0 shifts the focus toward restoring human involvement and promoting intelligent human-machine collaboration [105]. Collaborative robotics is a key enabler in achieving this synergy. Classification and Modes of Human-Robot Interactions (HRIs)  
According to [PERSON] et al. [106], human-robot interactions can be classified into four primary modes (Table 7):  
These modes describe increasing levels of integration and real-time dependency between human and robotic agents. The goal of collaborative robotics is to achieve seamless collaboration, where safety, ergonomics, and performance are harmoniously integrated. Standards such as ISO/TS 15066 support the safe implementation of collaborative applications [107]. Cobots are also classified based on design principles and safety mechanisms into [107]  
- Power and force limiting--low-powered and with rounded edges to ensure safety;  
- Hand-guided teaching--robots that learn motions by manual demonstration;  
- Speed and separation monitoring--obots that slow or stop based on human proximity;  
- Safety-rated monitored stop--temporary stops when humans enter the workspace. Design Principles and Methods  
Designing human-robot collaboration requires ergonomic integration, cognitive modeling, and ethical design. - Joint Cognitive Systems (JCS): A JCS is formed when humans and machines function as co-agents to achieve shared goals. Rather than treating the human and robot as isolated systems, the focus is on coordination patterns, adaptability, and co-agency [6]. [PERSON] and [PERSON] emphasize that these systems should be resilient and functionally adaptive in real-time [108]. - Actor-Network Theory (ANT): ANT views both humans and machines as actors (\"actants\") in a sociotechnical network. It offers tools to map how dynamic roles evolve in human-machine teams, treating machines not merely as tools but as integral agents [109]. - Concept of Operations (ConOps): ConOps provides a framework to define how humans and robots interact, collaborate, and share tasks within a system, specifying roles, responsibilities, operational scenarios, and performance expectations throughout the system's lifecycle [110]. \begin{table}
\begin{tabular}{c c} \hline \hline
**Type of Interaction** & **Description** \\ \hline Coexistence & The human and robot operate in the same area but without overlapping tasks. [106] \\ \hline Synchronization & Shared space, but tasks are performed at different times. [106] \\ \hline Cooperation & Simultaneous task execution in a shared space with different goals. [106] \\ \hline Collaboration & Joint execution of shared tasks, requiring real-time interaction. [106] \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Human–robot interaction (HRI) classification. Human System Integration (HSI): HSI focuses on aligning system functionality, design, and operation with human capabilities, limitations, and work contexts by systematically integrating human factors throughout all stages of the system's lifecycle [111]. Applications and Case Studies  
Table 8 presents key applications of human-robot interactions across various industries, highlighting their roles and benefits:  
Human-Centric Design Challenges  
- Cognitive load and mental models play a crucial role in human-centric design, as they influence how users perceive, interpret, and interact with automated systems.