IEEE Robotics & Automation Magazine - June 2021 - 85

-6
-4
-2
2
4
6
8
TIAGo
PA-10
10
12
14
2
4
6
8
-2
-4
-6
97.5 105 112.5 120 127.5 135 142.5 150 157.5 165
Time (s)
(a)
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.4
0.35
1
1.1
1.2
1.3
1.4
x-Axis (m)
(c)
Figure 11. The force/torque sensing-estimation and trajectory estimation during the cooperative loading task. (a) The interaction
forces during the cooperative transportation task. The leader's (mobile manipulator) interaction force as estimated by the follower
(static manipulator). (b) The actual ones are depicted. (c) The leader-estimated 2D trajectory and the actual one.
set of high-level tasks. Moreover, an important issue that we
have not yet addressed is the online reconfiguration of
planning in the presence of actuation or sensor faults,
which also mandates an increase in the number of involved
agents. Additionally, a significant attribute that we intend to
incorporate in the future pertains the aspects of cognitive
safety in human-robot collaboration tasks. More specifically,
we aim to tackle issues such as human situation
awareness and motion intention (inside the workspace) as
well as inherited compliant behavior during cooperative
manipulation tasks. In this way, we will be able to ensure
that robots and humans can safely and effectively coexist
in a real dynamic environment.
Conclusions
In this work, we propose a decentralized framework for the
efficient cooperation of heterogeneous robotic agents and
humans in manipulation and transportation tasks within
semistructured workspaces. This framework consists of separate
modules responsible for perception, motion, and manipulation
control, as well as high-level planning. We evaluated
the integrated system in a multitasking scenario involving
various heterogeneous robots and humans for the cooperative
loading/unloading and transportation of objects. A series of
metrics such as accuracy, ratio of success, and computational
cost justify the robustness, flexibility, and efficiency of the
overall framework.
JUNE 2021 * IEEE ROBOTICS & AUTOMATION MAGAZINE *
85
Actual Trajectory
Estimated Trajectory
1.5
1.6
1.7
105 112.5 120 127.5 135 142.5 150
Time (s)
(b)
Actual
Estimated
Transverse Force (N)
y-Axis (m)
Longitudinal Force (N)

IEEE Robotics & Automation Magazine - June 2021

Table of Contents for the Digital Edition of IEEE Robotics & Automation Magazine - June 2021

Contents
IEEE Robotics & Automation Magazine - June 2021 - Cover1
IEEE Robotics & Automation Magazine - June 2021 - Cover2
IEEE Robotics & Automation Magazine - June 2021 - Contents
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