ISO/TS 15066 is globally recognized as the guideline for designing safe collaborative robotic cells, where human and robot collaborate in order to fulfill a common job. Current approaches for implementing the ISO/TS 15066 guidelines lead to a conservative behavior (e.g. low velocity) of the robot and, consequently, to poor performance of the collaborative cell. In this paper, we propose an approach based on control barrier functions that allows to maximize the performance of a robot acting in a collaborative cell while satisfying the ISO/TS 15066 regulations. The proposed approach has been successfully validated both in simulation and through experiments.

SUMMARY: Industrial applications that involve working on and moving a heavy load or that constrain the operator to work in uncomfortable positions can take advantage of the assistance of a robotic assistant. In this paper, we propose an architecture for an ergonomic human–robot co-manipulation of objects of various shapes and weight. The object is carried by the robot and, thanks to an ergonomic planner, is positioned in the most comfortable way for the user. Furthermore, thanks to an admittance control with payload compensation, the user can easily adjust the position of the object for working on different parts of it. The proposed architecture is experimentally validated in a robotic cell including an ABB industrial robot.

In order to make robot programming more easy and immediate, walk-through programming techniques can be exploited. However, a modification of a portion of the trajectory usually means to execute the path from the beginning. In this paper we propose a passivity-based framework to modify the trajectory online, manually driving the robot throughout the desired correction. The system follows the initial trajectory, encoded with Dynamical Movement Primitives, by setting high gains in the admittance control. When the human operator grabs the end-effector, the robot becomes compliant and the user can easily teach the desired correction, until he/she releases it at the end of the modification. Finally, the correction is optimally joined to the initial trajectory, restarting the path tracking. To avoid unsafe behaviors, the variation of the admittance parameters is performed exploiting energy tanks, in order to preserve the passivity of the interaction.

In recent years, new programming techniques have been developed in the human-robot collaboration (HRC) field. For example, walk-through programming allows to program the robot in an easy and intuitive way. In this context, a modification of a portion of the trajectory usually requires the teaching of the path from the beginning. In this paper we propose a passivity-based method to locally change a trajectory based on a manual human correction. At the beginning the robot follows the nominal trajectory, encoded through the Dynamical Movement Primitives, by setting high control gains. When the human grasps the end-effector, the robot is made compliant and he/she can drive it along the correction. The correction is optimally joined to the nominal trajectory, resuming the path tracking. In order to avoid unstable behaviors, the variation of the control gains is performed exploiting energy tanks, preserving the passivity of the interaction. Finally, the correction is spatially fixed so that a variation in the boundary conditions (e.g., the initial/final points) does not affect the modification.