Advanced Robotics

Description

The activities of the team are aimed at developing intelligent robotic systems capable of operating in complex environments and in collaboration with humans. Research includes the use of artificial intelligence for human-robot interaction, with algorithms for perception, context understanding and adaptive planning. The research group also develops mobile collaborative robotics solutions, integrating autonomous navigation, safety and cooperation with human operators. At the same time, humanoid and quadrupedal robots are being studied and tested for applications that require advanced mobility, versatile manipulation, and natural interaction capabilities.
Technology transfer activities include collaborations with companies, prototyping, testing in industrial environments, specialized training and support for the adoption of emerging robotic technologies.

Programming a collaborative robot for handling flexible materials (EDIH4Marche project)

Publications

M. Polonara, X. Yang, L. Carbonari, X. Zhang: “VL-GRiP3: A hierarchical pipeline leveraging vision-language models for autonomous robotic 3D grasping”, Robotics and Computer-Integrated Manufacturing, 2026, 100, 103244. https://doi.org/10.1016/j.rcim.2026.103244
F. Neri, G. Palmieri, M. Callegari: “Non-holonomic mobile manipulator obstacle avoidance with adaptive prioritization”, Robotics, 2025, 14(4), 52. https://doi.org/10.3390/robotics14040052
F. Neri, G. Palmieri, D. Costa, M. Callegari: “Dynamic obstacle avoidance for non-holonomic mobile robots with differential wheels”, Mechanisms and Machine Science, 2024, 163, pp. 265–272. https://doi.org/10.1007/978-3-031-64553-2_31
D. Costa, C. Scoccia, M. Palpacelli, M. Callegari, D. Scaradozzi: “Design of a Labriform-Steering Underwater Robot through a Multiphysics Simulation Environment”, Robotics, 2022, 11(1), 11. https://doi.org/10.3390/robotics11010011
M. Callegari, L. Carbonari, D. Costa, A. Papetti, C. Scoccia: “Tools and Methods for Human Robot Collaboration: Case Studies at i-LABS”, Machines, 2022, 10(11), 997. https://doi.org/10.3390/machines10110997

Staff

Prof. Matteo Claudio Palpacelli
Tel. +39 071 220 4748
E-mail: m.palpacelli@staff.univpm.it

Prof. Luca Carbonari
Tel. +39 071 220 4418
E-mail: luca.carbonari@staff.univpm.it