As one of the guest editors, I am pleased to announce the Call for Papers for the Topical Collection on "Advancing Robotic Grasping and Manipulation for the Real-World" in the journal Autonomous Robots (AURO) from Springer Nature.
This collection aims to highlight cutting-edge research that advances autonomous robotic grasping and manipulation in unstructured, real-world environments. We particularly welcome contributions that help bridge the gap between lab prototypes and deployable systems.
We are looking forward to receiving your submission!
Call for Papers
This Topical Collection aims to showcase cutting-edge research advancing autonomous robotic grasping and manipulation within unstructured, real-world environments. The collection focuses on innovations that enable intelligent, robust, and scalable grasping and manipulation in real-world applications, such as industry, logistics and service robotics. It emphasizes strong perception, (learning-based) control, and flexible hardware, and encourages interdisciplinary approaches and real-world validations.
The scope is to narrow the gap between lab-bench prototypes and deployable systems. Therefore, contributions featuring experimental evaluations that clearly demonstrate the real-world robustness, practical feasibility, and generalizability across diverse real-world setups are strongly encouraged. By covering new algorithms, benchmarking techniques, simulation-to-reality transfer, and lifelong learning, this collection seeks to provide a comprehensive understanding of the current state and future directions in autonomous robotic manipulation.
Topics of interest include but are not limited to:
- Robust grasping and manipulation in real-world settings
- Learning-based perception and control
- Flexible and adaptive hardware for manipulation
- Simulation-to-reality transfer
- Benchmarking and evaluation methodologies
- Lifelong and continual learning for manipulation
- Real-world experimental validation in industry, logistics, and service robotics
- Foundation models for grasping and manipulation
- Human-robot object handovers
Who Should Submit?
This Topical Collection welcomes submissions from researchers, practitioners, and engineers working on:
- Academia: University researchers advancing robotic manipulation through novel algorithms, learning methods, or hardware designs
- Industry & Applied Robotics: Companies developing or deploying grasping systems in real-world production or logistics environments
- Interdisciplinary Teams: Researchers combining robotics, computer vision, machine learning, control theory, or mechanical engineering
- Early-stage & Established Work: Both breakthrough innovations and incremental improvements are welcome, provided they address real-world robustness and generalization
We particularly encourage submissions that demonstrate:
- Validated performance beyond simulation or controlled lab settings
- Reproducibility and scalability across different object types, environments, or robot platforms
- Solutions to practical challenges faced in industry, warehouses, or service roles
Important date
The deadline of submission is March 1, 2027.
Submission guidelines
See journal's guidelines for more details on how to prepare your manuscript, ethical standards and responsibilities, editorial and data policies, and other relevant information.
- Articles should be submitted with the journal submission system, Snapp (select our Collection on "Advancing Robotic Grasping and Manipulation for the Real-World" during submission).
- Submitted papers should present original, unpublished work, relevant to one of the topics of the Topical Collection.
- All papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation by at least 2 reviewers.
- This journal follows a single-blind reviewing procedure. Submissions will be reviewed on a first-come first-served rolling basis until the deadline, following the journal's review process and timelines.
- Accepted article will appear online in the webpage of the Topical Collection and will be published in a special issue of Autonomous Robots.
Guest editors
- Salvatore D'Avella, Scuola Superiore Sant'Anna
- Alessio Xompero, formerly at Queen Mary University of London
- Changjae Oh, Queen Mary University of London
- Berk Calli, Worcester Polytechnic Institute
- Kaiyu Hang, Rice University
- Andrea Cavallaro, EPFL
- Yu Sun, University of South Florida
For inquiries
For any inquiries regarding the Topical Collection, please contact the guest editor Salvatore D'Avella.