Kinetostatic danger field - a novel safety assessment for human-robot interaction

This paper presents a novel method for evaluating the danger within the environment of a robot manipulator. It is based on the introduced concept of kinetostatic danger field, a quantity that captures the complete state of the robot - its configuration and velocity. The field itself is invariant with respect to objects around the robot and can be computed in any given point of the workspace using measurements from the proprioceptive sensors. Moreover, all the computation can be performed in closed form, yielding compact algebraic expressions that allow for real time applications. The danger field is not only a meaningful indicator about the risk in the vicinity of the robot, but can also be fed back within control skills that implement some well known safety strategies like collision avoidance and virtual impedance control, provided that some environment perception is available in order to determine the points where the field should be computed. Kinematic redundancy for simultaneous task performance and danger minimization can be exploited. The methodology described in the paper is supported with simulation results.