Although the human factor is considered fundamental in the Industry 4.0 paradigm, apart from a few studies, the capabilities of collaborative robots to (i) perceive the work environment (including humans therein), (ii) represent it in a way to enforce safety and cooperation, and (iii) act sensibly alongside humans, have not been adequately developed.
WORKMATE aims at exploring a wide range of aspects to accelerate the transition from collaborative robots to robot workmates. On the one hand, a robot workmate is expected to be tasked with a dangerous, boring or stressful operation, whereas a human operator can supervise the process and intervene when needed. On the other hand, a robot workmate is expected to understand when human operators are stressed or tired, and adapt to them at different levels: on a qualitative level, it monitors human operators suggesting next actions and keeps them focused on the task at hand, tuning suggestions on the basis of such stress assessment; on a quantitative level, it perceives the workspace using perceptual categories grounding the human operator’s well-being principles, e.g., classifying objects on the basis of the difficulty for human operators to handle them.
WORKMATE targets four topics.
The traditional approach – according to which human-robot cooperation systems are developed – targets expert operators. This mindset must be re-thought, considering instead common people as the target users who will program and operate robots. This can be achieved by considering natural and intuitive robot programming approaches and interfaces, which do not require expert knowledge [TOPIC 1].
To favor the acceptability and trust of robots as workmates, it is important to enable a smooth interaction between humans and robots. This implies several aspects: human intention and human action recognition processes are of the utmost importance to adapt to the operator’s actions as they unfold [TOPIC 2]; robot motions and gestures should be not only safe but should also be aimed at enhancing human trust, following, e.g., bio-inspired patterns [TOPIC 3]; furthermore, robot behaviors and the communication between humans and robots should adapt to an operator’s cognitive and physical capabilities, as well as incipient fatigue and stress, by sharing autonomy accordingly and supporting the operator when needed [TOPIC 4].
We will identify and debate about key aspects related to the use, the acceptability, the trust and the benefits of human-robot cooperation systems. WORKMATE will foster discussion around such questions as:
- How can a robot understand operators actions, intentions and eventually their physical and mental status?
- What should a robot do to make its behavior understandable by the operator, therefore enforcing a sense of trust?
- How much information should the robot provide to the operator? What means of communication should the robot use?
- How much information does the robot need from the operator? What are the best ways to represent such knowledge?
- How can a non-expert operator communicate with the robot in a natural manner?
WORKMATE has received endorsements from the following IEEE Technical Committees:
- The IEEE-RAS Technical Committee on Cognitive Robotics.
- The IEEE-RAS Technical Committee on Automation in Logistics.
- The IEEE-RAS Technical Committee on Human-Robot Interaction & Coordination.
- The IEEE-RAS Technical Committee on Performance Evaluation & Benchmarking of Robotic and Automation Systems.