Article
Path Driven Dual Arm Mobile Co-Manipulation Architecture
for Large Part Manipulation in Industrial Environments
Aitor Ibarguren * and Paul Daelman
Citation: Ibarguren, A.; Daelman, P.
Path Driven Dual Arm Mobile
Co-Manipulation Architecture for
Large Part Manipulation in Industrial
Environments. Sensors 2021, 21, 6620.
https://doi.org/10.3390/s21196620
Academic Editors: Abolfazl Zaraki
and Hamed Rahimi Nohooji
Received: 23 August 2021
Accepted: 3 October 2021
Published: 5 October 2021
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4.0/).
Industry and Transport Division, TECNALIA, Basque Research and Technology Alliance (BRTA),
20009 San Sebastián, Spain; paul.daelman@tecnalia.com
* Correspondence: aitor.ibarguren@tecnalia.com
Abstract:
Collaborative part transportation is an interesting application as many industrial sectors
require moving large parts among different areas of the workshops, using a large amount of the
workforce on this tasks. Even so, the implementation of such kinds of robotic solutions raises
technical challenges like force-based control or robot-to-human feedback. This paper presents a
path-driven mobile co-manipulation architecture, proposing an algorithm that deals with all the steps
of collaborative part transportation. Starting from the generation of force-based twist commands,
continuing with the path management for the definition of safe and collaborative areas, and finishing
with the feedback provided to the system users, the proposed approach allows creating collaborative
lanes for the conveyance of large components. The implemented solution and performed tests show
the suitability of the proposed architecture, allowing the creation of a functional robotic system able
to assist operators transporting large parts on workshops.
Keywords:
mobile co-manipulation; force control; human-robot interaction; robotic application;
assistant robots
1. Introduction
The emergence of collaborative robotics is changing the way of developing new robotic
applications, especially in those cases involving cooperative tasks between humans and
robots. This kind of cooperative task raises many technical challenges, ranging from the
use of force feedback to guide the collaborative process [
1
] to the analysis of the social and
psychological aspects of the acceptance of these new technologies [2].
Robotic part transportation is a compelling application as many industrial sectors such
as the aeronautic [
3
,
4
] or automotive [
5
,
6
] require moving large parts among different areas
of the workshops, using a large amount of the workforce on tasks with no added value.
Therefore, the design and development of collaborative solutions based on flexible robotic
systems able to transport large pieces [
7
–
9
] would benefit a wide range of companies
worldwide. However, these systems need to deal with multiple technical topics like the
management of the force feedback to generate movement commands or the definition of
collaborative areas within the workshops where the robots can move freely.
This paper presents a path-driven dual-arm co-manipulation architecture for large
part transportation. This architecture addresses three key aspects of the collaborative part
transportation task: (1) Human-driven mobile co-manipulation, (2) soft superposition
of navigation trajectories to the co-manipulation task to ensure safety zones within the
workshop, and (3) robot-to-human feedback to guide and facilitate the collaborative task.
The architecture tackles these three topics, proposing a new scheme that addresses issues
for the industrial implementation of this kind of systems like safety and real-time feedback
of the process state. The implementation and evaluation of the architecture demonstrate its
suitability for cooperative applications in industrial environments.
The paper is organized as follows. Section 2 provides information about related
work. Section 3 presents the proposed architecture, including the different modules of
Sensors 2021, 21, 6620. https://doi.org/10.3390/s21196620 https://www.mdpi.com/journal/sensors
