Citation: Fei, J.; Chen, G.; Jia, Q.;
Liang, C.; Wang, R. Path Planning
Strategy for a Manipulator Based on
a Heuristically Constructed Network.
Machines 2022, 10, 71. https://
doi.org/10.3390/machines10020071
Academic Editor: Dario Richiedei
Received: 9 December 2021
Accepted: 12 January 2022
Published: 19 January 2022
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Article
Path Planning Strategy for a Manipulator Based on a
Heuristically Constructed Network
Junting Fei
1
, Gang Chen
1,
*, Qingxuan Jia
1
, Changchun Liang
2
and Ruiquan Wang
1
1
School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China;
feijunting@buptrobot.com (J.F.); spacerobot@163.com (Q.J.); wangruiquan@buptrobot.com (R.W.)
2
Beijing Key Laboratory of Intelligent Space Robotic System Technology and Applications,
Institute of Spacecraft System Engineering, Beijing 100094, China; Academiccabbage@163.com
* Correspondence: chengang_zdh@bupt.edu.cn
Abstract:
Collision-free path planning of manipulators is becoming indispensable for space explo-
ration and on-orbit operation. Manipulators in these scenarios are restrained in terms of computing
resources and storage, so the path planning method used in such tasks is usually limited in its oper-
ating time and the amount of data transmission. In this paper, a heuristically constructed network
(HCN) construction strategy is proposed. The HCN construction contains three steps: determining
the number of hub configurations and selecting and connecting hub configurations. Considering
the connection time and connectivity of HCN, the number of hub configurations is determined first.
The selection of hub configurations includes the division of work space and the optimization of the
hub configurations. The work space can be divided by considering comprehensively the similarity
among the various configurations within the same region, the dissimilarity among all regions, and
the correlation among adjacent regions. The hub configurations can be selected by establishing and
solving the optimization model. Finally, these hub configurations are connected to obtain the HCN.
The simulation indicates that the path points number and the planning time is decreased by 45.5%
and 48.4%, respectively, which verify the correctness and effectiveness of the proposed path planning
strategy based on the HCN.
Keywords: manipulator; path planning; work space
1. Introduction
Due to unique operational flexibility, manipulators are widely used in space explo-
ration and on-orbit operation [
1
–
3
]. To execute tasks quickly and accurately, manipulators
should be able to plan a path independently [
4
]. During the process, obstacles should be
taken into consideration for the safety of manipulators. Many scholars have studied this
problem in recent years.
On collision-free path planning of a manipulator, Dijkstra algorithm and A-star (A*)
algorithm are typically used algorithms [
5
–
7
]. Because the heuristic function introduced by
A* algorithm can indicate search direction for the points selection, A* algorithm has higher
efficiency than Dijkstra algorithm [
8
]. A* algorithm has been continuously improved by
many scholars since it was created. Trovato et al. [
9
] proposed an improved differential
A* algorithm, which can achieve better real-time performance than the traditional A*
algorithm. Das et al. [
10
] proposed an online path planning of mobile robots in a grid-
map environment using a modified real-time A* algorithm, which can minimize time,
energy, and distance while searching the path. Fu et al. [
11
] proposed an improved A*
algorithm, which can obtain a shorter and smoother path. The above research aims at
improving some characteristics of the A* algorithm, such as path search and reconstruction.
All of them search paths through grid-based maps by default. The grid-based map is
constructed by decomposing the work space of a manipulator into interconnected and
non-overlapping grids according to a certain granularity [
12
,
13
]. However, the side length
Machines 2022, 10, 71. https://doi.org/10.3390/machines10020071 https://www.mdpi.com/journal/machines
