Citation: Shi, W.; Wang, K.; Zhao, C.;
Tian, M. Obstacle Avoidance Path
Planning for the Dual-Arm Robot
Based on an Improved RRT
Algorithm. Appl. Sci. 2022, 12, 4087.
https://doi.org/10.3390/
app12084087
Academic Editors: Giovanni
Boschetti and João Miguel da Costa
Sousa
Received: 23 February 2022
Accepted: 17 April 2022
Published: 18 April 2022
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Article
Obstacle Avoidance Path Planning for the Dual-Arm Robot
Based on an Improved RRT Algorithm
Wubin Shi
1,2
, Ke Wang
2,
*, Chong Zhao
2
and Mengqi Tian
1,2
1
University of Chinese Academy of Sciences, Beijing 100049, China; shiwubin19@csu.ac.cn (W.S.);
tianmengqi19@csu.ac.cn (M.T.)
2
Key Lab of Space Utilization, Technology and Engineering Center of Space Utilization,
Chinese Academy of Sciences, Beijing 100094, China; zhaochong@csu.ac.cn
* Correspondence: wangke@csu.ac.cn
Abstract:
In the future of automated production processes, the manipulator must be more efficient to
complete certain tasks. Compared to single-arm robots, dual-arm robots have a larger workspace and
stronger load capacity. Coordinated motion planning of multi-arm robots is a problem that must be
solved in the process of robot development. This paper proposes an obstacle avoidance path planning
method for the dual-arm robot based on the goal probability bias and cost function in a rapidly-
exploring random tree algorithm (GA_RRT). The random tree grows to the goal point with a certain
probability. At the same time, the cost function is calculated when the random state is generated. The
point with the lowest cost is selected as the child node. This reduces the randomness and blindness of
the RRT algorithm in the expansion process. The detection algorithm of the bounding sphere is used
in the process of collision detection of two arms. The main arm conducts obstacle avoidance path
planning for static obstacles. The slave arm not only considers static obstacles, but also takes on the
role of the main arm at each moment as a dynamic obstacle for path planning. Finally, MATLAB is
used for algorithm simulation, which proves the effectiveness of the algorithm for obstacle avoidance
path planning problems for the dual-arm robot.
Keywords:
dual-arm robot; improved RRT algorithm; path planning; autonomous obstacle avoidance
1. Introduction
With the development of science and industrial automation, robot technology has
been greatly developed in recent decades, and gradually applied in military, aerospace,
industry, medical, service, and other fields [
1
,
2
]. Single-arm industrial robots have achieved
notable development and application in China, widely replacing manual casting, welding,
palletizing, and other operations [
3
,
4
]. However, many complex operational tasks require
collaboration between the robotic arms. The dual-arm robot has a larger working space,
stronger load capacity, and obvious advantages in heavy lifting and assembly scenarios.
However, unlike a simple combination of two single-arm robots, a dual-arm robot has some
overlap in its workspace. The path planning of two arms should not only consider static
obstacles in space, but also consider the interference between the two arms. In the field
of dual-arm robotics, how to realize obstacle avoidance motion planning is always a hot
issue [5,6].
In the field of robot path planning, many path planning algorithms have been formed.
The traditional methods mainly include the artificial potential field algorithm [
7
–
9
], the A*
algorithm [
10
,
11
], and the RRT algorithm [
12
,
13
], etc. The methods based on computational
networks mainly include neural network algorithms [
14
,
15
] and bioinspired planning
algorithms [
16
,
17
]. Bioinspired planning algorithms mainly include the genetic algorithm,
ant colony optimization (ACO), and so on. The genetic algorithm is an intelligent bionic al-
gorithm based on natural selection and genetic mechanisms [
18
]. The ACO is an intelligent
Appl. Sci. 2022, 12, 4087. https://doi.org/10.3390/app12084087 https://www.mdpi.com/journal/applsci
