Overview
This is a call for papers for a special issue titled “Robotics Perception in Adversarial Environments” in the journal Frontiers in Robotics & AI. This issue aims to explore advancements in robotics perception, particularly in challenging conditions where data quality is often compromised. The significance of this research lies in its potential to improve the performance of robotic systems in real-world applications, where environmental disturbances can severely impact data quality.
Background & Relevance
Recent advancements in sensor technologies and data-driven methodologies have propelled the field of robotics perception. However, many applications still face significant challenges when operating in unstructured environments, where low-quality visual data can lead to performance degradation. Understanding how to develop robust perception systems that can handle these adversarial conditions is crucial for the future of robotics, particularly in fields such as autonomous driving, agricultural robotics, and search and rescue operations.
Key Details
- Submission Deadlines:
- Abstract Submission (Soft deadline): October 15, 2019
- Manuscript Submission: January 31, 2020
- Publication Process: Rolling basis upon acceptance
- Guest Editors:
- Arturo Gomez Chavez, Jacobs University Bremen
- Dr. Christian A. Mueller, Jacobs University Bremen
- Dr. Amy Tabb, U.S. Department of Agriculture
- Dr. Max Pfingsthorn, OFFIS Institute
- Prof. Soeren Schwertfeger, ShanghaiTech University
- Dr. Enrica Zereik, CNR
- Prof. Francesco Maurelli, Jacobs University Bremen
- Submission Guidelines:
- Manuscripts should not exceed 12,000 words and can be submitted using LaTeX or Word templates.
- For detailed author guidelines, visit Frontiers Author Guidelines.
Eligibility & Participation
This call for papers is open to researchers and practitioners in the fields of robotics and computer vision. Contributions are welcome from those working on theoretical innovations, practical frameworks, and applications that address the challenges posed by adversarial environments.
Submission or Application Guidelines
Interested authors should prepare their manuscripts according to the provided guidelines and submit them by the specified deadlines. It is recommended to check if your institution has an existing membership with Frontiers, which may provide fee waivers for open-access publication.
Additional Context / Real-World Relevance
The exploration of robust perception technologies is vital as robotics increasingly integrates into various sectors, including agriculture, environmental conservation, and disaster response. This special issue aims to gather insights and advancements that can enhance the reliability and efficiency of robotic systems in unpredictable conditions, thereby contributing to the broader field of AI and robotics.
Conclusion
Researchers are encouraged to contribute to this special issue to share their findings and insights on robotics perception in challenging environments. This is an excellent opportunity to advance the discourse in this critical area of study and to impact real-world applications positively.
Category: CFP & Deadlines
Tags: robotics, computer vision, adversarial environments, deep learning, sensor technologies, machine learning, data-driven techniques, ICRA
