Safe Human-Robot Collaboration via Collision Checking and Explicit Representation of Danger Zones

Abstract

This paper deals with safe human-robot collaboration in the context of speed and separation monitoring paradigm. The core of the approach is to continuously track the separation distance between the robot and the human. The robot speed is then adjusted according to the perceived distance so that it will be able to stop before eventually come into contact with the human. We present an approach that aims at maximizing the productivity of the robot, i.e., its speed, while keeping the prescribed safety requirements satisfied. The method is based on explicit representation of danger zones -regions around the robot, where safety requirements are violated. The motion is then generated such that the robot moves as fast as possible, while its danger zone still does not collide with human operators. The approach is validated within an experimental study.Note to Practitioners-This article was motivated by the problem of maximizing productivity of the robotic manipulator while ensuring the safety of human collaborator. The increase in productivity is achieved by a faster traversal of predefined paths without compromising the safety of the human, which is specifically defined by industrial standard. The approach requires limited knowledge on robot's dynamical properties. More precisely, we only need the braking time as a "lumped" representation of robot's inertia. The underlying optimization problem is conveniently resolved by introducing danger zones that allow for intuitive visualization and geometrical representation of the regions around the robot that must be avoided. On the other hand, the method assumes the representation of humans via typical geometric primitives, which can be obtained using ofthe-shelf depth perception systems. The solution to the problem reduces to a repeated collision checking between danger zones and the human. Such an approach turns out to be suitable for real-time implementation due to availability of fast and efficient collision checking algorithms/libraries.

Human-Robot Role Arbitration via Differential Game Theory

“…It can be handled by measuring the height of the robot end-effector or directly by using a skeleton tracker if available. It is also possible to add danger zones as described in [88] and include them in the FL arbitration law. Of course, this approach should not consider the human arm that is directly in contact with the robot (if no co-manipulated object is considered).…”

A Control Architecture for Safe Trajectory Generation in Human–Robot Collaborative Settings

“…This strategy has been pursued, for instance, in [13] where robot links are represented as beams and an optimization problem is formulated which provides the velocity scaling factor and the joint velocity commands while guaranteeing a minimum human-robot distance and the fulfillment of physical robot constraints. This work has been recently extended in [14] to include an efficient method to compute danger zones in real-time, i.e., the 3D volumes corresponding to links of the robot where safety constraints are violated. Computing optimal smooth stop trajectories for collision avoidance has been addressed in [15], where the dynamics and torque limits of the robot are taken into account.…”

Collaborative robots in manufacturing and assembly systems: literature review and future research agenda

“…Recent studies assume the ergonomic index for tasks assigned to Cobots equal to zero (Stecke & Mokhtarzadeh, 2022;Li et al, 2022;Dalle Mura & Dini, 2022). However, this assumption neglects the fact that Cobots can create a new ergonomic load on workers (Lacevic et al, 2022;Lanzoni et al, 2022;Mura and Dini, 2023). In addition, some tasks can be done in different ways in the presence of cobot in supportive mode, so ergonomic indexes are not equal to zero.…”