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Subsequently, they have limited opportunities to be dexterous and push their physical and cognitive boundaries. This can affect their perceptions of what is a “fit” or “misfit” in this environment.

Human cognitive appraisals and emotional reactions are both essential to understanding what is considered a “fit” between the individual and their (physical and psychosocial) working ecosystem. Employees also need resources to efficiently perform their jobs, while simultaneously safeguarding their health and wellbeing.

In the world of maintenance, repair, and overhaul (MRO) approximately 3,500 expert human operators are killed annually, while 3.3 million non-fatal injuries also occur.

These are due neither to poor safety measures nor to human behavior. They are caused by the harsh environment and unforeseen events that occur. These include unpredictable faults and malfunctions with the processing equipment being operated, which dramatically increases the level of risk these skilled workers are exposed to. The likelihood of injuries does not exclusively occur during the maintenance of old infrastructure. The increasing number of large new plants is contributing to the increase in potential critical events. This factor has resulted in human workers being more exposed to the risk of injury or death.

The reason for this is simple. No other alternative has been able to provide the same level of advanced ability to strategically understand and cognitively adapt to this complex ecosystem that these workers operate in. To date, nothing can work or adapt as fast as a human.

Therefore, the mission of a typical robotics scientist should be to drastically reduce the risks that human operators face within the MRO value chain. They can do this by trying to place collaborative robots within the value chain equation.

I believe Europe should set a disruptive example for the whole world to follow by embracing these new working practices that use technology to ensure public health.

If they are able to accomplish these large technical and scientific leaps, we could see the mass adoption of collaborative robots used across a multitude of applications, from agriculture to energy generation.

The next generation of collaborative robots that we are likely to see will be equipped with physical and cognitive skills. For such robots to be effectively deployed on maintenance sites, there is a critical need to immediately understand working practices and operational constraints. They will need to capture the goals and constraints of the tasks, while minimizing the major overhaul that will take place for how the human workforce operates.

For humans and robots to collaborate successfully, the key barriers associated with how humans competently handle robots will need to be overcome. Above all, it is not reasonable to ask a human workforce to acquire skills in robotic programming or to automatically exchange information through coding. What is key for establishing these synergies between humans and robots is trust.

Over the next few years, natural language will be needed at the core of human-robot communications to ensure the frictionless adoption of robots in manufacturing. The large number of sensors that will need to be integrated into the next generation of robotic platforms could, in fact, enable voice processing. This includes speech-to-text and text-to-speech capabilities, plus voice tone analysis.

Ramping up the abilities for humans to comprehensively exploit robotic platforms still does not ensure that a strong bond will be established. For robots, being part of a team requires them to adapt their behavior to each individual user i.e. use human-like behavior to create a bond.

Initially, this will rely operationally on building robotic awareness through a multi-modal attention system that includes capturing voice, facial, and gait interpretations, along with more specific physiological parameters. The awareness of collaborative robots should then evolve into consciousness and improved behavioral skills by autonomously triggering the ability to finetune motivations and priorities over time. This would establish an unprecedented sense of empathy for humans and the ability to take over anytime there is a tangible difficulty or stress factor.

What is key for establishing these synergies between humans and robots is trust. This is extremely challenging to achieve. Over time, robots and humans will, however, establish relationships with one another.

I believe this should be the greatest priority for collaborative empathetic robots, along with how they care for humans.

The care provided should not just be physical, but also emotional. People should be placed at the center of this new robotic ecosystem. If successful, the support that robots provide could help enhance self-confidence for hundreds of thousands of human workers who face stressful working conditions on a daily basis.

More importantly, this will also provide relief for these workers by removing some of the risks they face by being exposed to dangerous situations. The extra abilities of these robots should not therefore challenge or scare human workers, but be seen as a means to enhance their work and support them.

Moreover, technological interventions that can support the adoption of future collaborative robots will significantly improve and help optimize the job quality that workers experience. This would create a workplace culture where robots are accepted as colleagues.

By taking inspiration from the behavioral and social sciences, and blending them with mechatronics and advanced computing, new transdisciplinary research branches will emerge. These will support the next generation of robotics scientists in developing collaborative empathetic robots.

Eventually, these robots will also mature into emotionally intelligent and interactive beings, which will lead to dramatic increases in both manufacturing productivity and worker satisfaction.