Synopsis of Industry 5.0 Paradigm for Human-Robot Collaboration

Abstract

This chapter explores the synopsis of the Industry 5.0 paradigm, focusing on Human-robot collaboration, encompassing critical elements from following the progression of evolution from Industry 4.0 to Industry 5.0 to the implementation of cutting-edge technologies and human-centric approaches within this framework. Industry 5.0 paradigm shift builds upon the foundation laid by Industry 4.0, with a renewed focus on integrating human intelligence and creativity with the capabilities of robots. The Operator of Industry 5.0 embodies the idea of skilled human operators working alongside automated systems to optimize performance and efficiency. Industry 5.0 technologies encompass collaborative robots (cobots) and advancements in robot learning, enabling safe and efficient collaboration between humans and machines and facilitating dynamic partnerships in shared workspaces. Human-centric approaches within Industry 5.0 technologies ensure that technological advancements align with human needs and preferences, fostering a work environment where humans and robots collaborate harmoniously. The concept of the Human Digital Twin offers a compelling instrument for identifying and optimizing human behavior within the context of Industry 5.0, enabling organizations to tailor processes and workflows to individual capabilities and preferences.

1. Introduction

Industry 5.0 (5IR) has been developed as the heir to Industry 4.0 (4IR), considering ecological and societal aspects [1]. The compliance of production techniques and their impact on the ecosystem are also important focal points within the 5IR paradigm [2, 3, 4]. According to the European Commission (EC) [1], 5IR signifies an expected evolution from 4IR, primarily emphasizing the driving forces behind European resilient, human-centric, and sustainable production. In opposition to the technology-centered method of 4IR, 5IR identifies a strong prominence on the worth of novel technologies while underscoring the significance of resilience, sustainability, and human-centricity in systems for generating value [5]. Scholars like Kusiak [6, 7] and Xu et al. [8] support the idea of resiliency in production, emphasizing the value-added perspective of 5IR. As per the EC [9], 5IR aims to create more inclusive workplaces, strengthen supply networks, and adopt ecologically responsive developed practices. Choi et al. [10] delve into the theme of “sustainable social well-being” concerning human-robot interactions (HRI) during the era of 5IR.

Zizic et al. [5] analyze the fundamental principles of 4IR and 5IR, emphasizing the pivotal roles of people, organizations, and technology in enabling their performance within a theoretical and practical framework. Ivanov [4], from a perspective of operations and supply chain management, presents a framework for 5IR. This framework considers feasible models for chain of supply, reconfigurable chains of supply, and human-centric environments, providing insights into societal, network, and plant-level considerations.

Within the process transformation and supply chain management framework, the principles and expertise associated with 5IR gain clarity when examined through the dimensions of resilience, sustainability, and human-centric approaches. Leng et al. [11] delineate three pivotal aspects of 5IR, which include prioritizing human needs and comfort, emphasizing environmental sustainability, and ensuring resilience in the face of potential adversities. Furthermore, Maddikunta et al. [12] present nuanced definitions and insights concerning 5IR, derived from reflections of experts and academics from various sectors. They further elaborate on potential applications and methodologies that could advance the adoption of 5IR. Despite the increasing focus on the technological aspects of the 5IR paradigm, a profound comprehension of this emergent concept remains imperative across management, organization, and technology [4, 5, 11, 12].

Nahavandi [13] emphasizes the fundamental difference between the two industries, highlighting the shift from mere robots to “cobots” in 5IR—robots collaborating with human operators. This viewpoint is echoed by Adel [14], defining 5IR as a paradigm shift rooted in human-machine collaboration. Correspondingly, Akundi et al. [15] note that 5IR’s primary trend is establishing human-robot workplaces and creating more innovative societies. Numerous researchers have explored human-robot collaboration (HRC) in the context of 5IR [16, 17, 18, 19].

This chapter lays out the synopsis of the 5IR Paradigm for HRC. First, the path from 4IR to 5IR is presented and followed by 5IR and its Operator. Second, 5IR knowledge and human-centric approaches within 5IR technologies are introduced. Finally, HRC, communication strategies in HRC, collaborative robots, and robot learning are depicted.

2. Following the progression from industry 4.0 to industry 5.0

The concept of 5IR was recently endorsed by the Directorate General for Research and Development (DGRD) of the EC, considering it not merely a sequential extension or alternative to 4IR but a forward-thinking extension that supplements the existing paradigm [20]. However, the 5IR theory outlined in several EC DGRD publications (e.g., [1, 20, 21]) places less emphasis on technological aspects and emphasizes the sustainability factor of the idea. Publications like Ref. [21] emphasize waste reduction, the circular economy, and decarbonization as fundamental characteristics of 5IR, although Breque et al. [20] criticize 4IR for fostering technological monopolies and neglecting current societal sustainability challenges.

The EC suggests that 5IR represents a vital progression from 4IR due to critical reasons [21]:

• 4IR does not align with the objectives of Europe 2030, as the existing digital economy fosters a winner-takes-all structure, resulting in significant wealth gaps and technological monopolies.

• 5IR is not solely a technological advancement; instead, it offers a broader perspective on 4IR, infusing a regenerative essence and orientation to the technical evolution of industrialized fabrication, emphasizing the interconnected welfare of society, the world, and wealth.

The key variations concerning 4IR and 5IR in progressive production are shown in Figure 1.

Figure 1.

Key variations concerning 4IR and 5IR in progressive production. (Adapted from: Xian et al. [22]).

As the evolution of 4IR continues, the emergence of 4IR has already begun to exert a significant influence on the production sector and is swiftly gaining attention in scholarly discourse [13]. The precise definition of 5IR still needs to be discovered, attributable to its recent introduction [15]. The conceptualization of 5IR arises from criticisms that 4IR overly emphasizes digitalization and AI-based technologies, neglecting the foundational tenets of social equity and sustainability [8]. This critique is supported by Maddikunta et al. [12], who argue that 5IR re-incorporates human labor into the manufacturing process, fostering the creation of higher-skilled employment opportunities. This paradigmatic shift seeks to move beyond the constrained HRI characteristic of 4IR, encouraging more cooperative, adaptable, and customized interactions within the context of 5IR [23].

Additionally, Muller [1] suggests that 5IR involves concepts and technologies like bioinspired technologies, energy efficiency, digital twins (DT), cybersecurity, and artificial intelligence (AI). However, the last three ideas are integral to 4IR and need to be distinctly characterized in 5IR. The industrial progression from 4IR-5IR is illustrated in Figure 2.

Figure 2.

Industrial progression from 4IR-5IR. (Adapted from: Adel [14]).

2.1 Industry 5.0

5IR prioritizes sustainability, emphasizing human-driven initiatives rooted in industrial production, encapsulated by the 6R’s policy: recognize, reconsider, realize, reduce, reuse, and recycle [24]. This framework aims to curb waste while enabling the creation of bespoke, high-quality products [12]. However, there needs to be more contention surrounding how 5IR’s strategy aligns with sustainable development [25]. Contrarily, it revolves around reintegrating humans into factories and fostering collaborative work with machines to enhance production efficiency by leveraging human cognitive abilities like creativity and knowledge in tandem with intelligent systems’ workflows [11, 12, 13]. Professionals in industries, IT experts, and researchers are urged to emphasize human factors in implementing 5IR’s new technological systems [11, 12].

From a technological standpoint, 5IR marks the “Social Smart Industry era,” intertwining social business networks with individuals for seamless communication. It is characterized by cyber-physical production systems (CPPS) synergizing with the human aspect [11, 12, 26]. Moreover, 5IR is human-centric, emphasizing collaborative work between humans and technologies like collaborative robots. Machines manage tasks that require significant labor or repetition, while humans supervise activities involving personalization and critical thought [12]. The alternative perspective describes 5IR as an innovation shaping the future of global governance, focusing on secure production outputs by segregating automation systems [12].

This concept repositions human agency within global industrial contexts, endeavoring to empower individuals through advanced technologies. The foundational premise is to integrate human centrality with systemic resilience and sustainability by facilitating the harmonization of machines and humans within industrial environments [11]. Nevertheless, the principles and theoretical frameworks of 5IR remain fluid, evolving, and comprehensive, grounded in these core tenets. The primary objective is to emphasize the welfare of workers in manufacturing processes, striving for a balance between human-machine collaboration while fostering resilience and sustainable development across environmental, economic, and social realms. Table 1 provides a comparative analysis of previous studies that significantly contributed to understanding 5IR.

Reference	Study type	Conception of 5IR	Key results and impacts
Özdemir and Hekim [28]	Conceptual	5IR evolves gradually, expanding upon the concept of 4IR.	5IR employs digital advancements such as big data and IoT to make knowledge accessible and guide society toward sustainable environmental advancement.
Nahavandi [13]	Conceptual	5IR represents an evolutionary advancement toward a harmonious relationship between humans and machines.	5IR endeavors to tackle the human-centered facet of sustainability, wherein collaborative robots work alongside operators rather than engaging in competition.
Longo et al. [26]	Empirical	5IR signifies a fresh transformation where CPPS merges with human operators to materialize CPPS, and human agents collaborate to establish the concept of symbiotic factories.	One of the crucial elements of 5IR is the focus on technology engineering that prioritizes values and ethics.
Xu et al. [8]	Conceptual	5IR is an evolving theory that supplements 4IR by fostering innovation to advance ecological and social principles.	Virtualization technologies and integration between humans and machines are essential components of 4IR. Attaining the sustainability objectives envisioned by 5IR could pose significant challenges.
Ivanov [4]	Conceptual	5IR is a complex occurrence that utilizes technological advancements, organizational strategies, and management approaches to advance sustainability.	5IR encompasses businesses, supply chains, and communities, prioritizing resilience in value creation, human-centricity, and societal requirements.
Ghobakhloo et al. [27]	Empirical	5IR is complementary to 4IR, leveraging the collaboration between society and industry to advance sustainability.	5IR has the potential to foster sustainable progress through a multifaceted mechanism that includes various sustainability functions like integrating value networks.
Huang et al. [29]	Conceptual	5IR is an innovative framework that utilizes flexible and compliant technological advancements to drive industrial expansion while prioritizing socio-environmental conservation.	5IR and Society 5.0 intersect, with both aiming for similar sustainability goals. Human-CPS, employment, virtualization, and the integration of humans and machines present opportunities and challenges for 5IR.
Leng et al. [11]	Conceptual	5IR is a vigorous and developing framework that strives for collaborative and stakeholder-oriented industrial progress.	5IR intersects with the concepts of 4IR, Society 5.0, and Operator 5.0. It embodies a comprehensive approach encompassing multiple industries and business sectors.
Maddikunta et al. [12]	Conceptual	5IR evolves by harnessing the innovative results of the collaboration between humans and machines.	5IR is primarily propelled by technology. A key objective of 5IR is achieving widespread customization. This study also delves into the foundational technologies of 5IR.
Sharma et al. [30]	Empirical	5IR signifies a groundbreaking and transformative innovation that redefines the manufacturing landscape, catalyzing a shift from a linear economic model to a circular economy.	The transformation of 5IR may encounter various technical facilitators and obstacles, including expenses, interoperability issues within systems, and the dissemination of inaccurate information.
Sindhwani et al. [31]	Empirical	5IR builds upon the foundations of 4IR, emphasizing collaboration between humans and robots, digital innovations, and regulatory measures to foster a digital bioeconomy that advances sustainability.	5IR depends on various technical facilitators, including bionics, virtual reality, digital twinning, and the internet of things (IoT).

Table 1.

Comparison of studies contributing to the conceptualization of 5IR. (Adapted from: Ghobakhloo et al. [27]).

2.2 Operator of industry 5.0

The advent of 4IR brought forth computerized and competent manufacturing approaches yet somewhat sidelined the welfare of workers. In this context, 4IR appears to overlook the human element. Conversely, in 5IR, the operator performs a strategic function in leveraging technology to enhance the quality of the work environment. This concept revolves around placing humans at the core of production processes, with technology supporting and empowering them. This fosters a harmonious interaction between individuals and machines, allowing human involvement to cooperate, merge, and effectively interact with emerging digital technologies [32].

With the advent of 5IR, the concept of Operator 5.0 has emerged, representing the next evolution of Operator 4.0, distinguished by enhanced resilience as encapsulated in the model of the Resilient Operator 5.0 [33]. Operator 5.0 may be categorized based on its objectives: One dimension involves a self-resilient operator who has evolved to mitigate inherent weaknesses and confront emerging challenges. At the same time, another focuses on system resilience, underscoring robust human-machine interactions [12]. Understanding the complexities of future industrial production systems, characterized by significant volatility, requires intricate and multifaceted decision-making capabilities from workers. Consequently, future operators must have human-centric technology and comprehensive training to control production and manufacturing systems [34]. It is essential to support employees of diverse experiences and backgrounds, with particular attention to the sustainability of the human workforce, including aging workers engaged in high-intensity tasks [34, 35].

2.3 Industry 5.0 technologies

The shift toward 5IR necessitates a socio-technical evolution, redefining the role of operators as the focal point of manufacturing and production systems. This evolution hinges on sophisticated strategies and approaches supported by progressive ICT [36]. 5IR principles can be applied across various aspects, spanning CPPS, data interoperability, and utilizing AI-based systems, 5G and 6G networks, augmented reality (AR), and collaborative robots to accomplish clever production methods [18, 37, 38, 39, 40, 41, 42, 43, 44, 45].

Introducing robotics into production systems boosts productivity, enhances workers’ well-being, and improves workplace health and safety [35, 36]. Collaborative robots working alongside humans capitalize on individual and technological capabilities, overcoming limitations in executing cumbersome, repetitive, and potentially hazardous tasks, enhancing workplace conditions, process repeatability, and reliability [46]. These robots assist in reducing low-value-added operations while enabling workers to focus on more advanced tasks requiring sensitivity, mental agility, adaptation, customization, and critical thinking [23, 36].

HRI necessitates continuous assessment of human factors to analyze and evaluate working conditions during these interactions [23]. A unique aspect of robotics is the advancement of DTs, high-fidelity, simulated representations that communicate in real time [42, 47]. These systems and simulation models optimize production and conduct safety tests [48]. DTs also promise to mitigate educational disparities by facilitating remote learning and training opportunities [49], potentially integrating into educational systems [48]. Interactive productive systems with robots further create learning environments [50].

However, 5IR raises concerns regarding safety and ethical issues in HRI [41, 51]. More stringent safety standards demand resilient safety approaches, guaranteeing increased dependability and adaptability in production through dynamic approaches from mutually human and robotic viewpoints [51]. Ethical concerns regarding the utilization of autonomous smart methods necessitate their prompt incorporation into the design phase of novel digital manufacturing methods [41, 52].

Amidst these developments, companies and industries should prioritize human-centered production processes by deploying consistent tools that enhance working environments and workers’ comfort [53]. Retaining and leveraging organizational memories and operators’ past experiences are vital for reusing successful practices [54]. To adopt the principles and advantages of 5IR, organizations must utilize 4IR digital technologies, such as CPS, big data, AI, DT, and collaborative robots [40]. The EC has outlined six directives for 5IR technologies, highlighting personalized HRI, advanced bio-inspired technologies, simulation and DT, data transmission, storage and analysis, AI, and technologies for environmental sustainability [40]. The architecture of 5IR advanced manufacturing is depicted in Figure 3.

Figure 3.

Architecture of 5IR advanced manufacturing. (Adapted from: Xian et al. [22]).

5IR has changed its focus from distinct technologies to a systemic approach, prioritizing societal well-being beyond growth and employment and placing worker welfare at the heart of production [8]. Nahavandi [13] envisions 5IR as a phase where humans rely on cobots as collaborators, enhancing efficiency, productivity, and cost savings while minimizing waste. The International Federation of Robotics (IFR) emphasizes that cobots are created to support human workers by handling strenuous and repetitive tasks. Other researchers echo similar views on enhancing ergonomics, productivity, safety, and affordability [55]. This shift aims to create more diverse job profiles, granting workers autonomy in task planning and decision-making and fostering effective human-cyber-physical systems [56].

Ensuring the well-being of workers in collaborative human-robot systems is crucial. Safety measures following ISO standards specific to industrial, personal, and collaborative robots are paramount. Control systems and collision detection mechanisms are pivotal in safe collaboration [57, 58]. Research focuses on AI applications controlling safety and ergonomic performance [59, 60, 61, 62].

Stress, workload, and trust are factors impacting operators’ performance in HRC [63]. Robots’ physical attributes and autonomous actions can cause mental stress and increased cognitive workload [64]. Trust plays a pivotal role; a lack of it can diminish an operator’s performance. Robot design elements can influence trust levels, emphasizing the importance of effective HRI.

2.4 Human-centric approaches within industry 5.0 technologies

The concept of human-centered manufacturing approaches is a fresh and contentious area that warrants clarity and thorough discussion. Nonetheless, this idea draws from ongoing research on human welfare, encompassing areas like Ergonomics, Operator 4.0, and HRC [65]. The trajectory of industrial production and manufacturing is steering toward 5IR, backed by the involvement of collaborative robots [66], AI, and cognitive computing technologies [14]. The integration of HRI serves as a technical catalyst for transitioning from digital system-oriented production to operator-centered production, fostering a digital production ecosystem that equally values human and robotic traits [67]. Effective interaction between humans and robots should optimize available resources for the benefit of production systems [67]. Implementing these cooperative methods also reduces demanding and monotonous tasks that might pose probable health and safety risks to workers, negating the necessity for investing in costly and intricate digital equipment [46]. AR stands as a tool to amplify the cognitive capabilities of humans and robots by seamlessly integrating humans into real-time and dynamic production systems [51]. Furthermore, assessing the effect of HRI proves challenging due to classical evaluation tools focusing solely on dynamic and static aspects, often overlooking crucial facts. Hence, current studies explore alternative assessment methods employing computerized and sensory systems for an additional comprehensive, innovative, and dynamic analysis [23].

A comprehensive overhaul of engineering education is imperative to foster sustainability and resilience across social, environmental, and economic dimensions within industries and firms. This reform aims to prepare future engineers with sophisticated technological skills, proficiency in data management, and a profound understanding of complex systems. The goal is to cultivate industries that are more resilient, sustainable, and attuned to human needs in the era of 5IR [68]. The future workforce must be able to discern and understand various production systems, enabling them to make informed choices among different operational models: those relying solely on human effort, those driven by technological capabilities, or those integrating both approaches. Consequently, engineering education should emphasize human-robot interaction (HRI), particularly focusing on the diverse methods of interaction and cooperation with emerging CPS [68]. Human-assisted learning strategies should also be implemented to manage and regulate automated additive manufacturing systems and error detection mechanisms within manufacturing processes [69, 70].

3. Human-robot collaboration

Advances in technology envision robots collaborating with humans in daily life. HRC involves a human and a robot working cognitively and physically together toward a common goal. This collaboration is pivotal in manufacturing, facilitating surveillance, prognostics, health management systems, and bolstering safety and sustainability in manufacturing processes [71, 72].

HRC aids in making critical decisions. Machines can assist in collecting information, evaluating uncertainty, and sharing crucial information with human decision-makers, potentially reducing cognitive loads. Furthermore, human decision-makers can argue their opinions with machine assistance, minimizing emotional influences [73].

As machines become more sophisticated, the relationship between humans and automation is transitioning from a “master-servant” dynamic to a “master-collaborator” one. This shift necessitates different approaches to system design, HRC, interfaces, and additional requirements for machines [74].

Current technological advancements are fostering physical interaction between humans and machines. This phase of HRI, mainly through the haptic channel, is termed HRC [75].

This development has led to the emergence of cobots, collaborative robots designed for human collaboration. These robots know human presence, prioritize safety, understand human goals and expectations, and learn tasks similar to humans [76, 77].

In human-centered production, advanced cognitive science and personalized AI suggest that empathic machines can sense human reactions, requirements, and partialities, providing situational assistance alongside cooperation [78].

Such circumstances may lead to reciprocal monitoring between humans and empathic machines, with the machine’s health measured quantitatively based on workload, task fluctuations, and more. This approach marks a new chapter in the human-machine relationship—human-machine empathy. Intimate interactions concerning humans and machines may foster continuous human-machine co-evolution, paving the way for new relationships centered on mutual enhancement rather than competition, shaping a better future for both machines and humans [79].

3.1 Communication strategies in human-robot collaboration

HRC has become a focal point in interdisciplinary research, concentrating on the cooperative efforts between humans and robots to achieve shared objectives [80]. HRC involves hypothetical and applied investigations into the investigation, plan, and assessment of robotic systems engaging with humans [81, 82, 83]. Interaction between humans and robots, a pivotal aspect of optimal HRC, has been extensively explored by researchers [63, 84, 85].

As a foundational step in HRC, communication methods can be categorized into tacit and specific forms. Gustavsson et al. outlined sophisticated interaction techniques, such as AR for spatial interaction, text-to-speech (TTS) technologies for verbal information, automatic speech recognition (ASR) for dictating tasks, and gestures for transmitting commands [84, 86, 87, 88]. Additionally, haptic feedback, virtual reality (VR), and audible sound systems were suggested to bridge communication barriers between construction workers and robots [81, 89, 90, 91, 92].

Berg et al. suggested enhancing communication through gestures and eye-tracking technologies, omitting speech recognition due to noisy environments and VR use limitations [63]. Explicit communication techniques primarily transmit specific information (e.g., distance, contact force), while biosensor-based methods have been explored to capture implicit signals (e.g., physiological data) [93, 94].

Numerous theoretical frameworks have been suggested to influence and enhance HRC, including Weiss et al.’s multi-level HRC framework, which integrates usability, social acceptance, user experience, and societal impact (USUS) factors [95]. Aaltonen et al., Johannsmeier, and Haddadin also presented theoretical frameworks focusing on refining collaboration levels between humans and robots [96, 97]. While these frameworks provide taxonomies for collaboration, they emphasize overall collaboration levels and lack detailed solutions for physical HRC.

3.2 Human digital twin (HDT) in the context of industry 5.0

HDTs are envisioned as digital replicas of individuals, crafted to complement human abilities, boost efficiency, unleash potential, and prioritize well-being within intelligent production systems [98, 99]. As a crucial technology within the framework of 5IR, HDTs forge explicit links concerning humans and technologies to amplify their capabilities, fostering seamless cooperation in advanced intelligent production environments. By leveraging real-time sensing, analysis, and automated feedback, HDTs reshape the dynamics of human-system integration, improving system design and execution while advocating for the sustainable advancement of personalized human skills. Integrating humans’ innate senses and cognitive capabilities into intelligent production systems through HDTs facilitates the conception of intricate and innovative industrial processes, ultimately enriching the manufacturing sector and cultivating more profound respect for future workers [100].

The evolution of HDT involves several stages, namely human digitalization awareness, enablement, involvement, and integration [101, 102, 103]. Human participation in the system spans various roles, from a passive spectator forced into the system to an active member providing information, an intelligent agent with complex responsibilities, and a program coordinator leading the system. The evolution of human digital depiction illustrates the interaction between physical and cyber systems, progressing from initial phases characterized by basic digital representations to more sophisticated 2D and 3D visualizations [104, 105].

Human factor indicators encompass human operators’ physical, psychological, and cognitive features. Physical guides include postures, workload, and efficiency, while psychological indicators encompass mental fatigue, concentration, and more. Cognitive indicators capture factors influencing human-system interaction, such as reasoning, memory, and motivation abilities. More detailed descriptions correlate with increased levels of indicators related to human factors.

Collaborating instruments, including tools and software, facilitate communication among humans, physical systems, and cyber systems. Human-machine interfaces have developed from early devices with controls and indicators to sophisticated visualizations on touch panels, motion capture devices, and X-reality interfaces that integrate virtual and physical worlds [106, 107].

HDT can contribute to innovation in industrial processes through human-centric design principles, focusing on creating technologies that enhance the well-being, satisfaction, and safety of workers. Davila-Gonzalez et al. [108] introduced a conceptual framework designed to enhance worker safety and well-being in industrial environments, such as oil and gas construction plants, by leveraging HDT cutting-edge technologies and advanced AI techniques. Wang et al. [109] presented a conceptual framework and system architecture of HDT from an Industry 5.0 perspective. Representative HDT applications in different lifecycle phases are presented including product design, production, optimization, and maintenance. As an example for production phase, an HDT system operator safety and worker management were proposed by Kim et al. [110] as illustrated in Figure 4. Mobile devices and motion capture equipment gather real-time location coordinates and musculoskeletal data to implement digital human modeling in virtual environments. This collected data is also utilized for analysis, including localization and posture detection for assessing worker safety via rule-based reasoning. Additionally, skeleton data processing aids in fatigue analysis using rapid upper limb assessment and standardizing work time. The resulting outputs, such as accident safety levels and fatigue-related work performance, assist shop floor workers in timely posture adjustments. This system enables safety managers to monitor shop floor workers and prevent potential accidents, while also supporting process managers in ensuring productivity and safety, particularly concerning musculoskeletal injuries.

Figure 4.

An HDT system for operator safety and work management. (Adapted from: Kim et al. [110]).

3.3 Collaborative robots (cobots)

Despite robots being utilized in industries for decades, 4IR has introduced highly connected robots capable of autonomous operation, playing an active role in various factories. In contrast, the 5IR generation anticipates a shift toward collaborative robots, or “cobots,” devised to operate with humans under their guidance. Enabled by advancements in digital technologies like AI, machine learning, and traditional robotics, cobots can sense and adapt to their surroundings, learning in real time. This adaptability renders them highly flexible, ideal for manufacturing small batch sizes, and meeting the demands of personalized products, a crucial aspect of future manufacturing. Unlike their predecessors confined within fenced environments, cobots are released to coexist, cooperate, and collaborate (3Cs) with human counterparts. These lightweight, precise, and easily programmable cobots can assist humans by handling physically demanding, hazardous, or repetitive tasks [111].

To guarantee human safety and build trust in robots, the industry has implemented regulations for CoBots by establishing safety standards for HRC. These standards govern the safe behavior of both practitioners and CoBots, providing direction for developing smart production systems. Notably, ISO 10218, categorized as a Type C technical standard, outlines safety design guidelines and obligations for protective measures in industrial robots. It details fundamental hazards associated with robotics and stipulates measures to eliminate or effectively mitigate them. Complementing ISO 10218 and ISO/TS 15066 introduces additional safety requirements for collaborative industrial robot systems and their work environments. Beyond safety standards, various technical solutions have been developed for preventive measures, focusing on collision detection, robot motion planning, and assessing risks associated with collaborative robots.

3.4 Robot learning

In the context of 4IR robotics, instructions involve collecting many images and posing data acquisition and programming challenges. However, 5IR introduces a paradigm shift where robots acquire motion skills through demonstrations, facilitating more flexible and precise human-robot cooperation [22]. Demonstrations can be conducted by either a robot or a human instructor. Human instructors offer the advantage of showcasing intricate and task-specific motions more easily than robot instructors. Consequently, the prevalent approach in advanced production is robot learning through human demonstrations. In 5IR, introducing humans into industrial manufacturing involves more intricate application scenarios. Therefore, cobots must exhibit flexibility and adaptability to various scenarios, leading to extensive research on transfer learning between different tasks. In a study [112], the robot’s acquired skills are generalized and applied to diverse tasks, enabling rapid adaptation to new learning tasks. This approach demonstrates that leveraging prior knowledge through knowledge transfer allows for higher expected returns with reduced exploration in the learning process.

4. Conclusions

The transition from 4IR to 5IR signifies a profound evolution in the dynamics of human-robot interactions, setting the stage for unprecedented collaboration and synergy. 5IR represents a paradigmatic shift toward human-centric methodologies within technological advancements, underscoring the necessity of integrating human intelligence and creativity with robotic capabilities.

In 5IR, operators exemplify skilled practitioners working with automated systems to enhance performance and efficiency. 5IR technologies are characterized by a synthesis of advanced innovations, including collaborative robots (cobots), robot learning, and communication strategies designed explicitly for HRC.

Within the framework of 5IR, human-centric approaches are prioritized to uphold the well-being and enhance the capabilities of human workers, ensuring that technological progress augments rather than supplants their roles. HRC emerges as a fundamental element of 5IR, fostering dynamic and productive partnerships where humans and robots strive collectively toward shared objectives.

Effective HRC communication strategies facilitate smooth interaction and coordination between humans and robots. Additionally, the HDT concept is vital for identifying and optimizing human actions within the 5IR context.

Collaborative robots, or cobots, illustrate the potential within 5IR to enable safe and effective cooperation between humans and machines in shared work environments. Concurrently, robot learning is advancing, allowing robots to adapt and learn from human interactions, thereby enhancing their effectiveness in dynamic settings.

The comprehensive vision of 5IR for HRC encapsulates a transformative agenda where humans and robots coalesce seamlessly, utilizing their strengths to drive innovation, efficiency, and prosperity in the digital era. As we embrace 5IR’s potential, we are propelled toward a future where human creativity and technological sophistication merge, redefining the prospects for both industry and society.