Symmetry-Inspired Approaches in Control, Robotics, and Intelligent Systems

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

Deadline for manuscript submissions: 31 October 2026 | Viewed by 435

Special Issue Editors


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Guest Editor
Faculty of Electronics and Communications Engineering, Universidad Veracruzana, Poza Rica 93390, Mexico
Interests: numerical and computational methods; fractional calculus; developing and implementing advanced strategies for dynamic system control; integrating artificial intelligence into embedded systems; optimizing algorithms based on fuzzy logic and machine learning
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Computer Science Department, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), San Andrés Cholula 72840, Mexico
Interests: signal processing; IoT; cybersecurity; artificial neural network; biomedical; circuit design

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Guest Editor
Facultad de Ingeniería en Electrónica y Comunicaciones, Universidad Veracruzana, Av. Venustiano Carranza S/N, Poza Rica 93390, Mexico
Interests: engineering; general mathematics; probability and statistics; signal and systems modeling; developing digital watermarking schemes; developing applications of fractional calculus for engineering problems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advances in control engineering, robotics, and intelligent systems increasingly leverage symmetric and asymmetric structures in both modeling and algorithmic design. Symmetry principles can be found in physical system dynamics, controller architectures, optimization frameworks, and learning-based decision mechanisms. Likewise, asymmetry may be intentionally introduced to enhance robustness, ensure stability under disturbances, or improve adaptability in uncertain and nonlinear environments.

This Special Issue aims to gather contributions that explore how symmetry—or deliberate asymmetry—can be exploited in the analysis, design, optimization, and implementation of control strategies, robotic systems, and intelligent decision-making algorithms. Both theoretical developments and practical applications are welcome, including methodologies based on fuzzy logic, neural networks, evolutionary computation, model-based control, hybrid AI techniques, and cyber-physical implementations.

Authors are invited to submit original research or review articles on (but not limited to) the following:

  • Symmetry-based modeling in dynamical and control systems;
  • Asymmetric control strategies for robustness and fault tolerance;
  • Intelligent control (fuzzy, neural, reinforcement learning);
  • Symmetric structures in adaptive, predictive, or optimal control;
  • Robotics and autonomous systems with symmetry-exploiting algorithms;
  • Symmetry in consensus, formation, and coordination control;
  • Bio-inspired and swarm intelligence with symmetric behaviors;
  • Symmetry/asymmetry in metaheuristic tuning of controllers;
  • Symmetric filters, observers, and estimation frameworks;
  • Mechatronic and cyber-physical systems with symmetric properties.

Dr. José R. García-Martínez
Dr. Alejandro Medina Santiago
Dr. Mario González-Lee
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

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

  • symmetry in control systems
  • asymmetric control strategies
  • intelligent control
  • fuzzy logic and neuro-fuzzy systems
  • model predictive control (MPC)
  • robust and adaptive control
  • reinforcement learning for control
  • evolutionary and metaheuristic optimization
  • robotics
  • multi-agent and swarm systems
  • cyber-physical systems
  • fault-tolerant and resilient control
  • bio-inspired and symmetry-based algorithms
  • system identification and dynamic modeling
  • motion planning and trajectory control
  • mechatronics systems

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Published Papers (1 paper)

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Research

22 pages, 2710 KB  
Article
An Inverse Kinematics Solution for Mobile Manipulators in Textile Workshops Based on an Improved Particle Swarm Optimization
by Wei Xie, Zhongxu Wang, Jiachen Ma, Jun Chen and Xingjian Xie
Symmetry 2025, 17(11), 1980; https://doi.org/10.3390/sym17111980 - 16 Nov 2025
Viewed by 251
Abstract
To enhance the operational performance of mobile manipulators in textile workshops and address the difficulty of inverse kinematics (IK) for this class of redundant manipulators, this paper leverages the robot’s structural symmetries and proposes a chaotic-mutation particle swarm optimization (CMPSO)-based IK algorithm for [...] Read more.
To enhance the operational performance of mobile manipulators in textile workshops and address the difficulty of inverse kinematics (IK) for this class of redundant manipulators, this paper leverages the robot’s structural symmetries and proposes a chaotic-mutation particle swarm optimization (CMPSO)-based IK algorithm for mobile manipulators, thus simplifying the solution process and ensuring balanced exploration of the search space. First, the coordinate–transformation relationships of the mobile manipulator are analyzed to establish its forward kinematic model. Then, a multi-objective constrained IK model is formulated according to the manipulator’s operating characteristics. The model incorporates a pose-error function, the ‘compliance’ principle, and joint-limit avoidance. To solve this model accurately, we refine the population initialization and boundary-violation handling of the particle swarm algorithm and introduce an asymmetric mechanism via an adaptive mutation strategy, culminating in a CMPSO-based IK solver. On this basis, single-pose IK tests and trajectory-planning experiments are conducted, and simulation results verify the effectiveness and stability of the proposed algorithm. Full article
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