Citation: Cui, C.; Park, C.; Park, S.
Physical Length and Weight
Reduction of Humanoid In-Robot
Network with Zonal Architecture.
Sensors 2023, 23, 2627. https://
doi.org/10.3390/s23052627
Academic Editors: Xiaochun Cheng
and Daming Shi
Received: 20 January 2023
Revised: 14 February 2023
Accepted: 24 February 2023
Published: 27 February 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Article
Physical Length and Weight Reduction of Humanoid In-Robot
Network with Zonal Architecture
Chengyu Cui , Chulsun Park and Sungkwon Park *
Department of Electronic and Computer Engineering, Hanyang University, Seoul 04763, Republic of Korea
* Correspondence: sp2996@hanyang.ac.kr; Tel.: +82-2-2294-0367
Abstract:
Recently, with the continuous increase in the number of sensors, motors, actuators, radars,
data processors and other components carried by humanoid robots, the integration of electronic
components within a humanoid is also facing new challenges. Therefore, we focus on the devel-
opment of sensor networks suitable for humanoid robots to designing an in-robot network (IRN)
that can support a large sensor network for reliable data exchange. It was shown that the domain
based in-vehicle network (IVN) architectures (DIA) used in the traditional and electric vehicles is
gradually moving towards zonal IVN architectures (ZIA). Compared with DIA, ZIA for vehicles
is known to provide better network scalability, maintenance convenience, shorter harness length,
lighter harness weight, lower data transmission delay, and other several advantages. This paper
introduces the structural differences between ZIRA and the domain based IRN architecture (DIRA)
for humanoids. Additionally, it compares the differences in the length and weight of wiring harnesses
of the two architectures. The results show that as the number of electrical components including
sensors increases, ZIRA reduces at least 16% compared to DIRA, the wiring harness length, weight,
and its cost.
Keywords:
robot sensor network; humanoid; zonal architecture; domain architecture; in-robot
network (IRN); in-vehicle network (IVN); zonal IRN architecture (ZIRA); domain IRN architecture
(DIRA); wiring harness; wiring length; wiring weight
1. Introduction
In the robotics research industry, different from general industrial robots, humanoids
manufactured for the purpose of realizing human appearance and behavior have a high
demand for the integration of electronics and mechanical construction. Compared with
industrial robots, humanoid robots need to have a higher awareness of the surrounding
environment, a larger range and accuracy of motion, and more intelligent interaction
capabilities [
1
–
7
]. In order to realize these requirements, along with the development of the
robotics industry, the focus of research has gradually shifted from mechanical construction
to electrical and electronic design. Atlas, a humanoid robot with agile movement ability, is
powered by an on-board computer to process the environmental data collected from light
detection and ranging (LiDAR), stereo camera, and laser range finder, and then transmit
control data to the hydraulic drives all over the robot’s body [
5
,
6
]. The interactive robot
Ameca is equipped with 27 motors on the head to achieve rich facial expression close to
human beings [
6
,
7
]. Therefore, during the development of humanoid robots, the number
and performance of core components such as various types of sensors, drivers, motors,
and processors are constantly increasing and improving, respectively. At the same time,
to realize the coordinated operation of these components, the research on the internal
communication network of the robot also known as in-robot network (IRN) is gaining more
attention [8–10].
In previous research, the idea of the IRN was proposed, and the network was divided
according to the domain structure according to the differentiation of sensors, environmental
Sensors 2023, 23, 2627. https://doi.org/10.3390/s23052627 https://www.mdpi.com/journal/sensors
