Citation: Ruiz-Ruiz, F.J.; Urdiales, C.;
Gómez-de-Gabriel, J.M. Estimation of
the Interaction Forces in a Compliant
pHRI Gripper. Machines 2022, 10,
1128. https://doi.org/10.3390/
machines10121128
Academic Editors: Shuai Li, Dechao
Chen, Mohammed Aquil Mirza,
Vasilios N. Katsikis, Dunhui Xiao and
Predrag S. Stanimirovic
Received: 26 October 2022
Accepted: 25 November 2022
Published: 28 November 2022
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Article
Estimation of the Interaction Forces in a Compliant
pHRI Gripper
Francisco J. Ruiz-Ruiz
1,
* , Cristina Urdiales
2
and Jesús M. Gómez-de-Gabriel
1
1
Robotics and Mechatronics Group, Escuela de Ingenierías Industriales, Universidad de Málaga,
29071 Málaga, Spain
2
Ingeniería de Sistemas Integrados Group, Escuela de Ingeniería de Telecomunicación, University of Málaga,
29071 Málaga, Spain
* Correspondence: fjruiz2@uma.es
Abstract: Physical human–robot interaction (pHRI) is an essential skill for robots expected to work
with humans, such as assistive or rescue robots. However, due to hard safety and compliance
constraints, pHRI is still underdeveloped in practice. Tactile sensing is vital for pHRI, as constant
occlusions while grasping make it hard to rely on vision or range sensors alone. More specifically,
measuring interaction forces in the gripper is crucial to avoid injuries, predict user intention and
perform successful collaborative movements. This work exploits the inherent compliance of a gripper
with four underactuated fingers which was previously designed by the authors and designed to
manipulate human limbs. A new analytical model is proposed to calculate the external interaction
forces by combining all finger forces, which are estimated by using the gripper proprioceptive sensor
readings uniquely. An experimental evaluation of the method and an example application in a control
system with active compliance have been included to evaluate performance. The results prove that
the proposed finger arrangement offers good performance at measuring the lateral interaction forces
and torque around the gripper’s
Z
-axis, providing a convenient and efficient way of implementing
adaptive and compliant grasping for pHRI applications.
Keywords:
physical human–robot interaction; underactuated grippers; kinodynamic finger model;
proprioceptive force sensing; interaction force calculation
1. Introduction
Physical human–robot interaction (pHRI) is a unique blend of human–robot interaction
(HRI) where robots interact physically with humans [
1
–
3
]. With the development of
cobots and force control schemes, this research topic of robotics has gained importance
over the years [
4
]. In some pHRI cases, robots and humans work in close proximity
without engaging in direct physical contact (e.g., object handover [
5
] or collaboration in
manufacturing activities [
6
]). Physical cooperation implies that both the human and robot
contribute to a common task, so safety and ergonomics become a priority [
7
]. In these cases,
humans provide cognitive capabilities (goal setting and decision making), while robots
provide power and precision [
8
]. Recently, there has been a trend toward applications
involving contact between humans and robots [
9
,
10
]. In this method, tasks like co-carrying
of solid objects [
11
], robotic balance assistance [
12
] or collaborative tooling [
13
,
14
] require a
proper estimation of the human intention, which is usually accomplished through analysis
of the human–robot interaction forces. In general, in applications such as rescues, human
augmentation, rehabilitation or assistance, robots not only need to touch humans but
even need to initiate contact sometimes [
15
–
17
]. Although some robots rely on special
terminals to touch humans (e.g., [
18
,
19
]), the general approach uses underactuated fingered
grippers. These grippers are fit for various tasks, such as manipulating human limbs [
20
].
Fully robot-initiated contact presents significant uncertainty. First, the human pose and
predisposition are not necessarily constrained. That aside, users might not comply to
Machines 2022, 10, 1128. https://doi.org/10.3390/machines10121128 https://www.mdpi.com/journal/machines
