US-12623347-B2 - Method for the safety control, during direct teaching, of a robotised system and relative robotised system

US12623347B2US 12623347 B2US12623347 B2US 12623347B2US-12623347-B2

Abstract

A method for the safety control, through direct teaching, of a robotised system comprises a learning step, wherein a processing unit determines a relative distance (RD) between at least one link (L) of the robot manipulator and an operator (O) and controls whether the relative distance (RD) of the at least one link (L) exceeds a predefined distance threshold value (TV); wherein the predefined distance threshold value (TV) is equal to or greater than the distance covered by the robot manipulator in the amount of time needed to stop starting from a respective maximum linear speed (VMAX); in case the relative distance (RD) is smaller than the predefined distance threshold value (TV), the method entails stopping the robot.

Inventors

Federica FERRAGUTI
Mattia BERTULETTI
Mattia GAMBAZZA
Matteo RAGAGLIA
Cesare FANTUZZI

Assignees

GAIOTTO AUTOMATION S.P.A.

Dates

Publication Date: 20260512
Application Date: 20220929
Priority Date: 20210929

Claims (12)

1 . A method for the safety control, during direct teaching, of a robotised system, the method comprising: a learning step, during which an operator (O) moves an end effector of a robot manipulator of the robotised system by means of a driving assembly and the movements made by the end effector are stored in a storage unit of the robotised system; wherein the robot manipulator comprises a plurality of links connected to one another through joints (J); wherein: during the learning step, a processing unit determines a relative distance (RD) between each link (L) of the robot manipulator and the operator (O) and controls whether the relative distance (RD) of the link (L) exceeds a predefined distance threshold value (TV); the predefined distance threshold value (TV) is equal to or greater than the distance covered by the robot manipulator in the amount of time needed to stop starting from a respective maximum linear speed (V MAX ); in case the relative distance (RD) is smaller than the predefined distance threshold value (TV), the method entails stopping the robot.
2 . The method according to claim 1 , wherein: the processing unit determines a relative speed (VR) between at least one link (L) of the robot manipulator and the operator (O), and controls that said relative speed (VR) is lower than a predefined threshold speed value (TV′); in particular, the processing unit determines the relative speed (VR) between each link (L) of the robot and the operator (O); and in case the relative speed (VR) exceeds the predefined threshold speed value (TV′), the method entails stopping the robot manipulator.
3 . The method according to claim 2 , wherein the predefined threshold speed value (TV′) is substantially equal to the maximum linear speed of the respective link (L).
4 . The method according to claim 2 , wherein: each link (L) comprises a first and a second end; and the relative speed (VR) between said at least one link (L) and the operator (O) is defined as the greatest of the relative speeds calculated between the operator (O) and the first or the second end of the link (L).
5 . The method according to claim 1 , wherein: the processing unit determines the position of the operator (O) based on a rigid link (L) between the operator (O) and the end effector of the robot manipulator, in particular between the operator (O) and the driving assembly, in particular based on the geometry of the driving assembly, which allows the operator (O) to move the robot manipulator.
6 . The method according to claim 1 , wherein: in order to determine the position of the operator (O) and of the at least one link (L), capsule and/or cylinder geometric models (GM) are used; in particular, each capsule (CA) is defined by a convex casing obtained by translating a respective ball between a first and a second end of a respective link (L) or of the operator (O).
7 . The method according to claim 6 , wherein the distance between two geometric models (GM) is calculated by subtracting the radii of each respective ball from the minimum of the distance between the respective first and second ends.
8 . The method according to claim 6 , wherein the operator (O) is modelled by means of one single geometric model (GM), in particular a capsule model (CA), which is considered as rigidly connected to the end effector of the robot manipulator based on the geometry of the driving assembly, which allows the operator (O) to move the robot manipulator.
9 . The method according to claim 1 , wherein the position of the operator (O) is determined relative to an inertial reference system, that is anchored to a base link (L) of the robot manipulator.
10 . The method according to claim 1 , wherein the driving assembly comprises a force/torque sensor; wherein the operator (O), during the learning step, exerts a force and/or torque upon the driving assembly, whose sensor detects an applied force and/or torque.
11 . A robotised system comprising: an end effector, which is configured to process or interact with an article being produced; a robot manipulator, which is movable with at least three degrees of freedom and on which the end effector is mounted; the robot manipulator comprising a plurality of joints (J) connected to one another through links; a control system, which comprises a storage unit and is configured to control the movement of the robot manipulator so as to move the end effector in the space; a driving assembly, which is configured to be operated by an operator (O) so as to transfer indications of movement to the robot manipulator; the driving assembly comprises a handling device, upon which, in use, the operator (O) exerts a force and torque; a sensor, which is designed to detect a force and torque applied to the handling device; and a processing unit, which is designed to provide Cartesian movement indications for the robot manipulator depending on the data detected by the sensor and following an admittance control; the storage unit is designed to store the movements made by the robot manipulator while the end effector is moved by the operator (O) by means of the driving assembly; the control system is designed to control the movement of the end effector based on the movements stored by the storage unit; the robotised system being configured so as to carry out the method according to claim 1 .
12 . The robotised system according to claim 11 and comprising a spraying head, which is configured to emit a jet of a substance to cover at least part of the surface of a ceramic article.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS The present invention is a 35 U.S.C. § 371 U.S. National Stage of PCT Application No. PCT/IB2022/059285, filed on Sep. 29, 2022, which claims priority from Italian Patent Application No. 102021000024905 filed on Sep. 29, 2021. The entire content of each of the aforementioned patent applications is incorporated herein by reference. FIELD OF THE ART The present invention relates to a method for the safety control, during direct teaching, of a robotised system, in particular comprising a robot manipulator, and to a related robotised system. The present invention finds advantageous, but not exclusive application in the field of ceramics, more particularly the glazing of ceramic articles, to which the following discussion will explicitly refer without losing its generality. BACKGROUND OF THE INVENTION In the field of processing ceramic articles, it is known to use robotised devices supporting spraying heads to paint and/or glaze surfaces. This type of approach, also used in other areas such as welding, positioning, polishing etc. is highly versatile and effective and has led to an increase in production speed and improvements in the repeatability and precision of the industrial process. In recent years, the use of industrial manipulators (hereafter also referred to simply as robots) has changed radically, moving from an idea of complete segregation of the workspace (obtained through physical barriers) to a scenario in which robots and human operators share the same workspace and also collaborate side by side. In this context, robots are becoming key elements in increasing the competitiveness of production, as the physical human-robot interaction (pHRI) can certainly help companies achieve a greater production flexibility to cope with rapidly evolving products. However, the widespread adoption of robotised technologies is still undermined by some well-known factors, including the inherently complex and time-consuming nature of robot programming. In view of the fact that a same robot can paint and/or glaze articles of different shapes, the way in which it is “taught” how to act has become an increasingly important working step and should be as simple and intuitive as possible. Traditional methods for programming industrial manipulators typically consist in using handhelds (teach pendants) for “point-to-point” programming (PTP) or in simulating the activity of the manipulator within an “offline” programming environment. In the former case, not only does the operator have to learn to use the teach pendant properly, but the intrinsic point-to-point programming style of these apparatuses is only efficient for particularly simple movements. In particular, the robot itself must be used to program the robot (i.e. a production stop is generated) and the programming is rather complicated (it is necessary to move the robot, at so-called “collaborative” reduced speeds, at every point of the path and save its position); and in order to be able to evaluate the goodness of the result, the program must be completed and then executed; if the result is not satisfactory, these operations must be repeated. In the second case (“off-line” programming), on the other hand, it is absolutely necessary to know the platform-specific programming language (and/or a dedicated programming environment, i.e. a dedicated IDE program), thus requiring specific and usually excessive knowledge from the human operator for the machine operator's task. The “off-line” and “PTP” programming methods are complex and laborious and this makes them particularly inefficient for the production of small and medium-sized batches. To overcome these shortcomings, direct teaching programming strategies generally defined as “walk-through” programming (also referred to as “lead-through” or “manual guidance” programming) have been developed, with the most diverse practical applications, such as spraying or welding. These programming strategies are characterized by the fact that the operator grasps the manipulator and manually leads it in the desired positions, without any prior knowledge of the specific programming language and/or of the functions offered by the specific handheld (teach pendant). During the learning step, a control unit (hereinafter also called a controller) of the robot records the intermediate points or the entire trajectory imposed by the human operator, so that the manipulator itself can subsequently reproduce this desired movement independently. Generally, direct teaching programming architectures are based on two key elements: a detection system (sensor) and an admittance (or impedance) control algorithm managed by the control unit (or controller). The detection system is responsible for measuring the interaction forces/torques exerted by the operator on the manipulator. The aforesaid objective can be achieved mainly in two ways: by exploiting the direct detection of the torque at the joints of the manipulato