TCRA

Understanding the environment in which a robot interacts or collaborates with their human counterparts is very important to establish affective interaction. Over the years, we  have focused on the perception of human non-verbal cues with the help of a vision–based robot perception system. The highest level of perceptual features of our vision system  include the recognition of human facial expressions, body posture and personality traits. Higher-level features of the acoustic system include speech-to-text transcription,  semantic representation as well as sentiment analysis of the robot-directed speech.
Therefore, an important step towards natural communication is the understanding of changing human activities. This enables the robot to interpret the movements of a  communication partner and react in an adequate way. Robots are growing to be more prevalent in automation factories with an expectation of 20 million manufacturing jobs  being substituted with robots by the year 2030. As the future aspires robots and humans to function in parallel, these aspects of optimal interaction play a vital role in task  collaboration between human and robot. Modern requirements of industrial manufacturing require a significantly higher level of flexibility and autonomy of robotic systems  than the current ones, as well as a qualitatively higher level of robot intelligence and the possibility of human-robot or robot-robot communication. This includes the use of  collaborative robotic systems of the new generation characterized by biologically inspired humanoid structure (with body segmentation), higher levels of intelligence and  expertise as well as the use of intuitive multi-modal interface (use of speech, gestural symbolism, messaging, etc.) for mutual more efficient communication. Collaborative  robotics is a field of research in robotics that engages a robot working in close proximity with a human co-worker to achieve a useful task in a shared space. The International  Federation of Robotics (IFR) defines 4 collaboration levels between robots and human co-workers, namely, co-existence, sequential collaboration, cooperation, and responsive collaboration. These collaborative robots, i.e. Co-bots, with anthropomorphic traits are becoming more prevalent with research supporting how human-like qualities in the robot  increases the human co-worker’s inclination to work alongside said robots. Co-bots improve the productivity by balancing the need for safe and flexible execution of the  task. The need for set guidelines and prior research in the field of collaborative robotics arises from the dynamic and uncertain nature of the human co-worker's behaviour. A  robot can be programmed to do a task or a set of tasks repeatedly, but human beings are deemed incapable of the same behaviour. A collaborative robot must thus be capable  of successfully finishing the assigned task whilst being able to adapt to this changing human behaviour. To bridge the gap of behaviour mismatch between the two agents for  task completion is therefore an essential area of research. At the moment of the world pandemic caused by the Covid-19 virus, there is an increasing need to construct robotic  systems that should replace human auxiliary work in technological operations in which the participation of two or more workers is necessary, such as the assembly of bulky  items or processing with tools that require multiple auxiliary operations at the same time. The ultimate goal to be achieved in this project by developing a collaborative  humanoid robot for industrial purposes is greater flexibility of production as well as substitution of human labour in technological tasks where interactive work of two or more  workers is necessary. Industrial production, sustainable even in the conditions of large pandemics, can be achieved by minimizing degree of mutual contacts between human  workers and by substituting them by collaborative robots.