Intelligent Control and Learning for Biomimetic Robotics
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 15 August 2026 | Viewed by 4
Special Issue Editors
Interests: dynamic stability and multi-modal design of intelligent bionic flying robots; high-lift mechanisms and takeoff–landing coupled dynamics of flapping-wing flying organisms
Special Issues, Collections and Topics in MDPI journals
Interests: aerodynamics; swarm robotics; control strategy; intelligent material; actuation control; multi-modal perception; bio-inspired structure
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Biomimetic robotics take inspiration from biological systems to create adaptive, efficient machines that operate in complex environments. This Special Issue focuses on promoting the integration of intelligent control systems with bio-inspired robotic structures and mechanisms, highlighting the synergy between hardware design and adaptive control. We invite contributions that address novel control architectures, learning algorithms, and mechanically intelligent designs for biomimetic robots, including adaptive and learning-based control, neural networks, reinforcement learning, sensorimotor integration, bio-inspired locomotion and manipulation, swarm robotics, and morphological computation. Submissions exploring soft robotics, compliant mechanisms, variable-structure designs, and embodied intelligence from both control and mechanical perspectives are particularly welcome. This Special Issue aims to showcase interdisciplinary research that bridges intelligent control theory, robotic mechanism design, and biological principles, ultimately driving innovations in autonomous, agile, and adaptive robotic systems.
Dr. Chao Liu
Dr. Huan Shen
Dr. Zhujin Jiang
Guest Editors
Manuscript Submission Information
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Keywords
- biomimetic robotics
- intelligent control
- bio-inspired mechanisms
- adaptive control
- reinforcement learning
- soft robotics
- morphological computation
- sensorimotor learning
- swarm robotics
- embodied intelligence
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