Symmetry/Asymmetry in Autonomous 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 35
Special Issue Editors
2. Instituto Superior de Investigaciones Biológicas (INSIBIO), Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), San Miguel de Tucumán, Argentina
3. Department of Electrical Engineering, Federal University of Sergipe, São Cristóvão, Brazil
Interests: human-robot interaction; mobile robotics; sensing systems; image processing; computer vision
Special Issue Information
Dear Colleagues,
Symmetry, broadly defined as the invariance of a system under transformations such as rotation, reflection, or, in some cases, translation, is a fundamental concept in both natural and artificial systems. In robotics, symmetry supports efficient design, locomotion, manipulation, and perception by leveraging balanced configurations and predictable dynamics. Conversely, asymmetry opens up opportunities for adaptability, customization, and optimized performance, particularly in unstructured environments. This Special Issue explores the role of symmetry and asymmetry in autonomous robotics, with a focus on their impact on system architecture, control strategies, perception, and interaction. Topics of interest include symmetrical and asymmetrical robotic designs, motion planning and control algorithms, sensor placement optimization, and the influence of symmetrical/asymmetrical features on machine learning models for autonomous decision making. We invite theoretical, experimental, and review contributions that address the interplay of symmetry and asymmetry in robotics to further our understanding and development of autonomous systems.
Dr. Eduardo Freire
Guest Editor
Dr. Humberto A. Secchi
Guest Editor Assistant
Manuscript Submission Information
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Keywords
- symmetry in robotics
- asymmetry in autonomous systems
- robotic locomotion and manipulation
- motion planning algorithms
- sensor placement optimization
- perception of autonomous robots
- control strategies for robotics
- machine learning in robotics
- human–robot interaction
- adaptive robotic design
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