Papers

3

Total Citations

19

H-Index

3

About

Alessandro Mosca is a leading researcher in human-robot collaboration, with a focus on developing safe and efficient control systems for industrial and teleoperated environments. His most cited work, an advanced dual Active Power Filter (APF)-based controller, addresses the critical challenge of simultaneous collision and singularity avoidance in human-robot collaborative assembly processes, earning 11 citations since 2023. This contribution is pivotal for enabling robots to work alongside humans without compromising safety or productivity. Mosca also made notable contributions to teleoperation, co-authoring a training simulator for robots deployed at CERN, which has been cited 4 times. His research bridges theoretical control algorithms with practical applications in high-stakes settings like particle physics laboratories. By integrating real-time obstacle detection and path planning, Mosca’s work enhances the reliability and autonomy of robotic systems, directly impacting manufacturing and remote operations. His achievements underscore a commitment to advancing human-robot interaction, making him a key figure in the field of collaborative robotics.

Research Focus

Key Achievements

3
H-Index
3
Papers
19
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
An advanced dual APF-based controller for efficient simultaneous collision and singularity avoidance for human-robot collaborative assembly processes
11 citations · 2023
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of Applied Sciences and Arts of Southern Switzerland, European Organization for Nuclear Research

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago