Ezio Bassi
Papers
7
Total Citations
102
H-Index
6
About
Ezio Bassi is a leading researcher in robotics and control systems, with a focus on sliding mode control, cooperative robotic systems, and the Industrial Internet of Things (IIoT). His most influential work, "A Supervisory Sliding Mode Control Approach for Cooperative Robotic System of Systems" (2013, 46 citations), introduces a novel framework for managing distributed, heterogeneous robotic networks, enabling robust coordination in complex environments. Bassi has also made significant contributions to hybrid position/force control for manipulators, as seen in his 2009 paper (17 citations), which enhances contact reliability by integrating force sensor dynamics into control schemes. His research extends to IIoT-based efficiency monitoring, exemplified by his 2016 work on Gantry robots (13 citations) and subsequent studies on motion control in automated warehouses (7 citations), bridging the gap between theoretical control and industrial application. Additionally, his earlier work on trajectory tracking (2002, 9 citations) adaptively improves performance in position-controlled manipulators. With over 100 total citations, Bassi’s work is foundational for advancing autonomous, interconnected robotic systems in manufacturing and logistics.
Research Focus
Key Achievements
Top Papers
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- 3IIoT based efficiency monitoring of a Gantry robot13 citations · 2016
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- 6IIoT-based Motion Control Efficiency in Automated Warehouses7 citations · 2019
- 7