Scheduling, Planning, Decision and Games in Intelligent Dynamic Robotics

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 386

Special Issue Editors

School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, China
Interests: adaptive control; stochastic control; intelligent control; decision control; optimal filtering; Bayesian estimation; statistical learning; swarm intelligence; target tracking; task planning; aerospace systems; space operation; autonomous unmanned systems
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Guest Editor
School of Computer & Communication Engineer, University of Science and Technology Beijing, Beijing, China
Interests: intelligent system; internet of things; artificial intelligence; big data; data science

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Guest Editor
School of Electrical Engineering, Southwest Minzu University, Chengdu, China
Interests: intelligent control; artificial intelligence

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Guest Editor
The School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Dongchuan Road No. 800, Shanghai 200240, China
Interests: design and evaluation of spaceborne GNSS receiver for multiple missions; weak GNSS signal acquisition & tracking; ultra-tight coupled GNSS/Inertial technology in space; autonomous real-time orbit determination onboard; nonlinear Kalman Filter technology; nonlinear estimation and control of time-delayed systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the past several decades, robotic systems in multiple domains, including ground, airborne, spaceborne, submarine, and other special industrial robots, are taking on increasing requirements related to the intelligence of performing various tasks, so that the relevant control theory and techniques of the dynamic robotics show a clear trend to combine with operations research and intelligent computation, generating decision-based planning and scheduling solutions for robotic tasks in complex environments.

This Special Issue is devoted to recent advances in intelligent decision and control related to the analysis and use of symmetries in multidisciplinary areas of dynamic robotics. The Special Issue aims at providing a way for people studying in mathematics, computer science, information science, system engineering, or other fields to disseminate their findings about symmetries. Papers on the topics of interest, including but not limited to the listed keywords, are solicited.

Dr. Yuankai Li
Dr. Zhiguo Shi
Dr. Yulian Jiang
Dr. Xiaoliang Wang
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • symmetric robotics
  • sensing and control
  • information fusion
  • data analysis
  • Bayesian optimization
  • stochastic operations
  • game theory
  • reinforcement learning
  • neural networks
  • task allocation
  • trajectory planning
  • swarm intelligence
  • multi-agent system
  • ground-based mobile robots
  • unmanned aerial vehicles
  • flying robots
  • space robots
  • submarine robots
  • deep space exploration vehicles
  • navigation, guidance and control

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Published Papers (1 paper)

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Research

17 pages, 1315 KiB  
Article
Research on Navigation and Dynamic Symmetrical Path Planning Methods for Automated Rescue Robots in Coal Mines
by Yuriy Kozhubaev, Diana Novak, Roman Ershov, Weiheng Xu and Haodong Cheng
Symmetry 2025, 17(6), 875; https://doi.org/10.3390/sym17060875 - 4 Jun 2025
Viewed by 52
Abstract
In the context of coal mine operations, the assurance of work safety relies heavily on efficient autonomous navigation for rescue robots, yet traditional path planning algorithms such as A and RRT exhibit significant deficiencies in a coal mine environment. Traditional path planning algorithms [...] Read more.
In the context of coal mine operations, the assurance of work safety relies heavily on efficient autonomous navigation for rescue robots, yet traditional path planning algorithms such as A and RRT exhibit significant deficiencies in a coal mine environment. Traditional path planning algorithms (such as Dijkstra and PRM) have certain deficiencies in dynamic Spaces and narrow environments. For example, the Dijkstra algorithm has A relatively high computational complexity, the PRM algorithm has poor adaptability in real-time obstacle avoidance, and the A* algorithm is prone to generating redundant nodes in complex terrains. In recent years, research on underground mine scenarios has also pointed out that there are many difficulties in the integration of global planning and local planning. This paper proposes an enhanced A* algorithm in conjunction with the Dynamic Window Approach (DWA) to enhance the efficiency, search accuracy, and obstacle avoidance capability of path planning by optimizing the target function and eliminating redundant nodes. This approach enables path smoothing to be performed. In order to ensure that the requirement of multiple target point detection is realized, an RRT algorithm is proposed to reduce the element of randomness and uncertainty in the path planning process, leading to an increase in the convergence rate and overall performance of the algorithm. The solution to the problem of determining the global optimal path is proposed to be simplified by means of the optimal path planning algorithm based on the gradient coordinate rotation method. In this study, we not only focus on the efficiency of mobile robot path planning and real-time dynamic obstacle avoidance capabilities but also pay special attention to the symmetry of the final path. The findings of simulation experiments conducted within the MATLAB environment demonstrate that the proposed algorithm exhibits a substantial enhancement in terms of three key metrics: path planning time, path length, and obstacle avoidance efficiency, when compared with conventional methodologies. This study provides a theoretical foundation for the autonomous navigation of mobile robots in coal mines. Full article
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