Increase human-robot awareness for a better cooperation in a collaborative environment
Collaborative robotics has an increasing trend in the automation industry and is expected to keep increasing in the following years. Up to now, companies use mostly collaborative robots (cobots) as standard robots but without fences, since they are light and with ergonomic shapes so they are not able to
create any harm to the human operator.
This is unluckily a very sub-optimal usage of cobots since their main advantages are not limited to safety measures but are also endowed with high flexibility in the production process.
This means that they can be combined with the dexterity of a human to achieve the most flexible system possible while at the same time they can be easily reprogrammed by a non-skilled operator.
This research aims at making the human-robot interactions more integrated both from a robot programming point of view, making the robot intuitive to use, and from a collaborative point of view, making the collaboration as natural and seamless as possible. This is possible thanks to a complete digitalization of all the components of the workspace: the robot, the human, the manipulated objects and the executed tasks.
It is indeed paramount to provide more awareness to the robotic agent both about the environment it is in (human, objects, ...) and the task it needs to perform (programming). Consequently, it is necessary to gather all the possible information coming from the environment or human task demonstrations and
digitalise them to enhance the robot’s perception.
In light of the above, my research project is focused on creating an architecture that can make human-robot collaboration easier to achieve and, at the same time, gives a straightforward interface to reprogram the robot to perform a different task.
The architecture provides first the operator with an easy interface to program the robot task through Sequential Flow Chart (SFC) or Virtual Reality (VR). After the programming phase, the architecture grants error detection, notification through an interface of such errors and flexible robotic tasks planning.
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