Citation: Stravopodis, N.; Valsamos,
C.; Moulianitis, V.C. Experimental
Verification of Optimized Anatomies
on a Serial Metamorphic Manipulator.
Sensors 2022, 22, 918. https://doi.org/
10.3390/s22030918
Academic Editors: Xiaochun Cheng
and Daming Shi
Received: 31 December 2021
Accepted: 20 January 2022
Published: 25 January 2022
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Article
Experimental Verification of Optimized Anatomies on a Serial
Metamorphic Manipulator
Nikolaos Stravopodis *, Charalampos Valsamos and Vassilis C. Moulianitis *
Department of Products and Systems Engineering, University of Aegean, 81100 Ermoupolis, Syros, Greece;
balsamos@syros.aegean.gr
* Correspondence: dpsdd17103@syros.aegean.gr (N.S.); moulianitis@aegean.gr (V.C.M.);
Tel.: +30-22810-97000 (V.C.M.)
Abstract:
The inherit complexity of the determination of the optimal anatomy and structure to task
requirements and specification for metamorphic manipulators poses a significant challenge to the
end user, as such methods and tools to undertake such processes are required for the implementation
of metamorphic robots to real-life applications in various fields. In this work, the methodology for
an offline process for the determination of the optimal anatomy maximizing performance under
different requirements is presented. Such requirements considered in this work include the kinematic,
kinetostatic and dynamic performance of the manipulator during task execution. The proposed
methodology is then applied to a 3 D.o.F. metamorphic manipulator for different tasks. The presented
results clearly show that a single metamorphic structure is able to provide the end user with different
anatomies, each better suited to task specifications.
Keywords:
serial modular metamorphic manipulators; optimal anatomy determination; anatomy to
task matching; kinematic tasks; dynamic tasks
1. Introduction
As robots become increasingly incorporated in human life and activities, so are robotic
tasks becoming increasingly complex and challenging. Since the beginning of their im-
plementation, robots have been closely linked to manufacturing and industrial activities,
where most tasks that were undertaken by their usage were relatively easy to model and
plan. While these tasks were becoming increasingly complex, the challenge was addressed,
utilizing advanced sensing and control techniques, to overcome certain limitations of the
robot’s anatomy. However, as the task pool moved on to include a multitude of tasks from
various sectors of application (such as medicine, space, human care, etc.), their complexity
increased almost exponentially. Coupled with the need for high adaptability and high
performance, it soon became evident that robot design was required to move from the
typical fixed anatomy systems to implement the reconfigurability paradigm so as to provide
the additional capability of matching the robot’s anatomy to a task in an optimal fashion,
thereby addressing the new requirements.
The incorporation of modularity and reconfigurability allowed for the design and
production of various proposed robotic manipulator systems that provided end users with
a highly adaptable and cost-effective system, since a modular reconfigurable robot may be
loosely characterized as a “multiple anatomy system”. The new design paradigm allowed
the end user to structure the best anatomy to match a given task such that the manipulator
can achieve the best possible performance during its execution. It is beyond the scope
of this work to present the multitude of different proposed design approaches and the
subsequent proposed systems implementing this design paradigm; however, thorough
reviews with extensive information and system presentation may be found in [1–3].
Although modularity and reconfigurability have been attained in the relevant liter-
ature as a most promising approach, the efforts to overcome certain barriers still present
Sensors 2022, 22, 918. https://doi.org/10.3390/s22030918 https://www.mdpi.com/journal/sensors
