Kinematics, Motion Planning and Control of Robotics
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".
Deadline for manuscript submissions: 10 February 2025 | Viewed by 320
Special Issue Editors
Interests: mechatronics; robotics; control systems
Interests: robotics; mechatronics; metal forming; hydraulic and pneumatic driving systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Kinematics, motion planning, and robotics control are essential fields in modern engineering and technology. These areas are driving innovations that are transforming industries and everyday life. As robots become more integrated into sectors such as manufacturing, healthcare, and service industries, the importance of precise and efficient motion control is crucial. Kinematic analysis provides the foundation for understanding robot movements, while advanced motion planning algorithms enable robots to navigate complex environments seamlessly. Robust control mechanisms ensure that these systems operate reliably and accurately, even in dynamic and unpredictable settings.
This Special Issue aims to explore the latest innovations and research in kinematics, motion planning, and control of robotic systems. We are interested in contributions that push the boundaries of current knowledge and address the following (and related) themes:
- Innovative kinematic models and their applications in robotics.
- Advanced motion planning techniques for autonomous systems.
- Robotics control in dynamic environments.
- Development and application of anthropomorphic and redundant robots.
- Integration of AI, including fuzzy logic and neural networks, in robotics control.
- Real-time control strategies and their implementation.
- Multi-robot coordination and collaborative robotics.
- Enhancing human–robot interaction for safer and more efficient systems.
- Applications in specialized fields such as medical robotics, agricultural automation, and service robotics.
- Use of machine learning for improved robotics control and motion planning.
We invite original research articles that provide new insights and practical solutions, as well as review papers that summarize recent developments and emerging trends in these critical areas. Through this collection, we aim to foster a deeper understanding and spark innovative ideas that will shape the future of robotics.
Dr. Mihai Crenganiş
Prof. Dr. Sever-Gabriel Racz
Prof. Dr. Radu-Eugen Breaz
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 100 words) can be sent to the Editorial Office for announcement on this website.
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. Applied Sciences is an international peer-reviewed open access semimonthly 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
- kinematics
- motion planning
- robotics control
- anthropomorphic robots
- redundant robots
- AI in robotics
- fuzzy logic
- neural networks
- autonomous systems
- multi-robot coordination
- human–robot interaction
- dynamic environments
- real-time control
- medical robotics
- agricultural automation
- service robotics
- advanced algorithms
- machine learning
- collaborative robotics
- innovative kinematic models
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