Human Robot Integration (HRI)  
Advances in the field of robotics is enabling the development of machines with increased computational intelligence, exploiting their embodied “physical" intelligence. Inspired by neuroscientific models of human behavior in interaction with the physical world, the new robots can safely touch humans and physically act in the environment. New sensing and display tools will bring other senses than just vision to share information on the world between a robot and a human. The fusion of such technologies, together with deeper understanding of how to interface humans and machines, is enabling a new relationship between humans and robots, that is much more of an integration than an interaction in the classical sense.

Human-Machine Teaming (HMT) is an emerging field that involves the collaboration between humans and machines to achieve a common goal. With the rapid development of intelligent systems, HMT has become an important research area in both academia and industry with the goal to improve performance, reliability, and safety in complex systems by combining the unique capabilities of humans and machines. The term HMT refers to a wide range of human-machine collaborations, from simple interactions between a single human and a single machine, to complex multi-agent systems involving multiple humans and multiple machines. The success of HMT depends on the ability of humans and machines to communicate effectively and work together seamlessly. To achieve this, HMT employs a range of techniques from diverse fields such as engineering, computer science and psychology. One key aspect of HMT is the design of interfaces that allow humans to interact with machines in an intuitive and efficient manner. This involves developing interfaces that take into account human cognitive and physical limitations, as well as machine capabilities and limitations. HMT also studies how humans perceive and respond to machine-generated information, and how this information can be presented in a way that is easy to understand and use. Another important aspect of HMT is the concept of shared autonomy, which is the development of algorithms and systems that enable machines to work effectively with humans and in which both parties contribute to the control and decision-making process. In shared autonomy, the human and machine work together to achieve a common goal, with the machine providing assistance and support to the human, while the human retains control and oversight. Shared autonomy is an important area of research in robotics, as it allows robots to be used in situations where complete autonomy is not practical or desirable, such as in medical applications where a human surgeon needs to remain in control of the procedure. More broadly, HMT includes developing machine learning algorithms that can adapt to human behaviour and preferences, and decision-making algorithms that can take into account human input and feedback. HMT has many practical applications, including aviation, healthcare, transportation, and defence. For example, in aviation, HMT can be used to develop intelligent cockpit interfaces that help pilots make better decisions in complex and dynamic environments. In healthcare, HMT can be used to develop intelligent medical devices that can assist healthcare professionals in diagnosing and treating patients. Human-Machine Teaming is an exciting and rapidly evolving field that has the potential to revolutionise many aspects of our lives. By leveraging the strengths of both humans and machines, HMT can help us to solve complex problems, improve efficiency and safety, and enhance our overall quality of life.


Research Line: 
Trustworthy Artificial and Embodied Intelligence