Collision-free robotic manipulation: a review and bibliometric analysis
Martinez Peral, F.J.,Ferez Rubio, J.A.,Mronga, Dennis,de Gea Fernández, José,Segura Heras, J.V.,Perez Vidal, C.
International Journal of Systems Science   (2025)
Ed. Taylor & Francis  ISSN:0020-7721  DOI:https://doi.org/10.1080/00207721.2025.2547392

Resumen:

This study presents a comprehensive review and bibliometric analysis of collision-free robotic manipulation, a key area for ensuring safety and optimising efficiency in advanced robotics. A data set was collected from the Web of Science Core Collection (2014–2024) and subjected to analysis, with 169 articles, with the aim of identifying emerging trends, key contributions and global collaboration patterns. The results demonstrate a steady increase in scientific output and identify four research clusters: collision avoidance in robotic systems, trajectory planning and optimisation, reinforcement learning and autonomous planning, and collaborative robotics and safety. These clusters illustrate the convergence of advanced techniques such as trajectory planning, optimisation algorithms and autonomous learning. This highlights their influence on both industrial applications and collaborative environments. This study provides a comprehensive overview of the research landscape, facilitating a deeper understanding of the field and fostering interdisciplinary collaboration.