Voxel-based Space Monitoring in Human-Robot Collaboration Environments

In today's industry, production processes are more oriented towards customer customization, demanding manufacturing plants to be increasingly flexible, where Human-Robot Collaboration (HRC) plays an important role. To fully take advantage of this collaboration, both robot and human need to perceive each others actions and intentions, operating accordingly. Thus, the typical collaborative environment that is nowadays monitored only for safety purposes needs to evolve into a more transparent, informative and attainable concept in order to give human-like perception to the robot. This paper proposes a voxel-based space monitoring approach in collaborative robotics environments, where distinct technologies are combined to form a labeled occupancy voxel-grid (LOG), i.e, a three-dimensional grid with labels for all the critical elements of the collaborative environment. A stereo vision camera is used to capture the supervised space in a point cloud, to then create an unlabeled voxel-grid. Making use of the RGB frames, both human and robot joint positions are located (using OpenPose and robot controller), pinpointing the positions of other significant elements in collaborative tasks as well. These positions are used to label the base voxel-grid. With the composition of the collaborative space provided in the grid, not only typical obstacle avoidance can be achieved, but also more advanced topics like predictive control or task recognition. Overall, this approach provides a much higher perception of the collaborative environment, enabling a more symbiotic relation between human and robot in collaborative robotics.