Full Text:   <242>

CLC number: 

On-line Access: 2023-09-27

Received: 2023-03-03

Revision Accepted: 2023-08-25

Crosschecked: 0000-00-00

Cited: 0

Clicked: 207

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/FITEE.2300151


An anti-collision algorithm for robotic search-and-rescue tasks in dynamic unknown environments


Author(s):  Yang CHEN, Dianxi SHI, Huanhuan YANG, Tongyue LI, Zhen WANG

Affiliation(s):  School of Computer Science, Peking University, Beijing 100871, China; more

Corresponding email(s):   chenyang20@stu.pku.edu.cn, dxshi@nudt.edu.cn

Key Words:  Rescue and search, Reinforcement learning, Game theory, Collision avoidance, Decision-making


Yang CHEN, Dianxi SHI, Huanhuan YANG, Tongyue LI, Zhen WANG. An anti-collision algorithm for robotic search-and-rescue tasks in dynamic unknown environments[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .

@article{title="An anti-collision algorithm for robotic search-and-rescue tasks in dynamic unknown environments",
author="Yang CHEN, Dianxi SHI, Huanhuan YANG, Tongyue LI, Zhen WANG",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="-1",
number="-1",
pages="",
year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2300151"
}

%0 Journal Article
%T An anti-collision algorithm for robotic search-and-rescue tasks in dynamic unknown environments
%A Yang CHEN
%A Dianxi SHI
%A Huanhuan YANG
%A Tongyue LI
%A Zhen WANG
%J Journal of Zhejiang University SCIENCE C
%V -1
%N -1
%P
%@ 2095-9184
%D 1998
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2300151

TY - JOUR
T1 - An anti-collision algorithm for robotic search-and-rescue tasks in dynamic unknown environments
A1 - Yang CHEN
A1 - Dianxi SHI
A1 - Huanhuan YANG
A1 - Tongyue LI
A1 - Zhen WANG
J0 - Journal of Zhejiang University Science C
VL - -1
IS - -1
SP -
EP -
%@ 2095-9184
Y1 - 1998
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2300151


Abstract: 
This paper deals with the search-and-rescue tasks of a mobile robot with multiple interesting targets in an unknown dynamic environment. The problem is challenging due to the complexity of multi-objective and unpredictable moving obstacle behaviors. In this paper, to ensure that the mobile robot avoid obstacles properly, we propose a mixed-strategy Nash equilibrium–based Dyna-Q (MNDQ) algorithm. First, a multi-objective layered structure is introduced to simplify the representation of multiple objectives and reduce computational complexity. This structure divides the overall task into subtasks, including searching for targets and avoiding obstacles. Second, a risk-monitoring mechanism is proposed based on the relative positions of dynamic risks. This mechanism helps the robot avoid potential collisions and unnecessary detours. Then, to improve sampling efficiency, MNDQ is presented, which combines Dyna-Q and mixed-strategy Nash equilibrium. By utilizing mixed-strategy Nash equilibrium, the agent makes decisions in the form of probabilities, maximizing the expected rewards and improving the overall performance of the Dyna-Q algorithm. Furthermore, a series of simulations are conducted to verify the effectiveness of the proposed method. The results show that MNDQ performs well and exhibits robustness, providing a competitive solution for future autonomous robot navigation tasks.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE