Matteo Ragaglia

About

Matteo Ragaglia is a leading researcher in human-robot collaboration (HRC) and safe industrial automation. His work centers on enabling fluid, safe interaction between humans and robots in shared workspaces, with a particular focus on trajectory generation, human motion prediction, and sensor-based perception. Ragaglia’s most cited paper (93 citations) introduces a trajectory generation algorithm that uses multiple depth sensors to ensure safe collaboration, a foundational contribution to the field. He also co-authored a highly influential state-of-the-art review on robotics in construction (68 citations), highlighting his impact beyond manufacturing. His work on sensorless lead-through programming (56 citations) and robot learning from demonstrations (52 citations) has advanced intuitive robot programming, while his safety-aware trajectory scaling algorithm (43 citations) integrates human occupancy prediction to prevent collisions. Ragaglia has also contributed to wearable haptic controllers for teleoperation (26 citations) and multi-camera human detection systems (9 citations). His research consistently addresses the core challenge of HRC: balancing productivity with worker safety. With over 400 total citations, Ragaglia’s work is essential reading for anyone interested in the future of collaborative robotics, particularly in industrial and construction settings.

Research Focus

Key Achievements

Top Papers

1. 1
   Trajectory generation algorithm for safe human-robot collaboration based on multiple depth sensor measurements

   93 citations · 2018
2. 2
   Robotics in the Construction Industry: State of the Art and Future Opportunities

   68 citations · 2018
3. 3
   Accurate sensorless lead-through programming for lightweight robots in structured environments

   56 citations · 2015
4. 4
   Robot learning from demonstrations: Emulation learning in environments with moving obstacles

   52 citations · 2017
5. 5
   Safety-aware trajectory scaling for Human-Robot Collaboration with prediction of human occupancy

   43 citations · 2015
6. 6
   A Novel Wearable Haptic Controller for Teleoperating Robotic Platforms

   26 citations · 2017
7. 7
   Integration of perception, control and injury knowledge for safe human-robot interaction

   22 citations · 2014
8. 8
   Path-Tracking Controller for Tracked Mobile Robot on Rough Terrain

   12 citations · 2019
9. 9
   Multiple Camera Human Detection and Tracking inside a Robotic Cell - An Approach based on Image War, Computer Vision, K-d Trees and Particle Filtering

   9 citations · 2014
10. 10
    Detecting, tracking and predicting human motion inside an industrial robotic cell using a map-based particle filtering strategy

    7 citations · 2015

Key Collaborators

Contact & Links