Advances in Kinematic Planning and Dynamic Control of Intelligent Robots
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 15 December 2025 | Viewed by 57
Special Issue Editors
Interests: non-linear control; sliding mode control; intelligent robots; high-precision control; vehicle dynamics and control
Special Issues, Collections and Topics in MDPI journals
Interests: state estimation and locomotion planning of humanoid robot
Special Issue Information
Dear Colleagues,
The field of robotics is undergoing a paradigm shift driven by advancements in computational algorithms, sensor technologies, and adaptive control systems. Kinematic planning and dynamic control lie at the heart of enabling robots to perform complex tasks in unstructured environments, from industrial automation and autonomous navigation to medical robotics and human–robot collaborations. These foundational disciplines ensure precise motion execution, stability in dynamic interactions, and adaptability to real-world uncertainties.
This Special Issue aims to consolidate cutting-edge research on the integration of kinematics and dynamics in order to address challenges such as real-time motion planning, multi-degree-of-freedom optimization, robustness in dynamic environments, and energy-efficient control. By bridging theoretical models with practical implementations, this Special Issue seeks to advance robotic systems toward higher autonomy, safety, and versatility.
The scope of this Special Issue aligns with the Electronics journal’s focus on innovative technologies and computational methodologies. We invite original research and review articles that explore novel approaches, algorithms, and applications. In this Special Issue, original research articles and reviews are welcome. Research areas include, but are not limited to, the following:
- Kinematic path planning for multi-joint and mobile robots.
- Dynamic modeling and control of robotic manipulators and legged systems.
- Real-time trajectory optimization under environmental constraints.
- Machine learning-driven motion planning for adaptive robotics.
- Collision avoidance in dynamic or cluttered environments.
- Human–robot interaction with emphasis on safety and compliance.
- Sensor fusion for enhanced localization and control accuracy.
- Energy-efficient actuation and torque optimization.
- Multi-robot coordination and swarm dynamics.
- Simulation frameworks for validating kinematic and dynamic models.
We look forward to receiving your contributions.
Dr. Ke Shao
Dr. Bin Lan
Guest Editors
Manuscript Submission Information
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Keywords
- robotic kinematics
- dynamic control
- motion planning
- trajectory optimization
- autonomous robotics
- sensor fusion
- real-time systems
- multi-robot coordination
- adaptive algorithms
- human–robot interaction
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