Leonardo Sabatino Scimmi

About

Leonardo Sabatino Scimmi is a robotics researcher whose work sits at the dynamic intersection of collaborative robotics, human-robot interaction, and autonomous systems for precision agriculture. With over 290 citations across his key publications, Scimmi has established himself as a significant voice in advancing safe, intelligent robotic systems capable of operating alongside humans in real-world environments. His most celebrated contribution is the "Agri.q," a solar-powered unmanned ground vehicle (UGV) designed for precision agriculture, which garnered 62 citations and demonstrated his ability to bridge robotics engineering with sustainable, practical field applications. Equally influential is his sustained work on collision avoidance, developed progressively from foundational algorithms in 2017 through increasingly sophisticated vision-based systems fusing data from multiple depth sensors — research that directly addresses one of collaborative robotics' most critical safety challenges. Scimmi has also made notable strides in human-robot handover control and workspace-sharing frameworks, developing architectures where robots and human operators fluidly exchange roles as givers and receivers. His more recent exploration of artificial potential field methods for mobile robot navigation signals a broadening research vision. Throughout his career, Scimmi's work consistently prioritizes practical implementation, safety, and real-time performance — qualities essential for robotics to move meaningfully from laboratory settings into industry and agriculture.

Research Focus

Key Achievements

Top Papers

1. 1
   Design of a UGV Powered by Solar Energy for Precision Agriculture

   62 citations · 2020
2. 2
   A Practical and Effective Layout for a Safe Human-Robot Collaborative Assembly Task

   47 citations · 2021
3. 3
   Vision‐based control architecture for human–robot hand‐over applications

   40 citations · 2020
4. 4
   Collison Avoidance using Point Cloud Data Fusion from Multiple Depth Sensors: A Practical Approach

   30 citations · 2019
5. 5
   Implementing a Vision-Based Collision Avoidance Algorithm on a UR3 Robot

   29 citations · 2019
6. 6
   Experiments on the Artificial Potential Field with Local Attractors for Mobile Robot Navigation

   19 citations · 2023
7. 7
   Design of the positioning mechanism of an unmanned ground vehicle for precision agriculture

   18 citations · 2019
8. 8
   Collision Avoidance Algorithm for Collaborative Robotics

   17 citations · 2017
9. 9
   Experimental Real-Time Setup for Vision Driven Hand-Over with a Collaborative Robot

   17 citations · 2019
10. 10
    Human Arm Motion Tracking by Kinect Sensor Using Kalman Filter for Collaborative Robotics

    14 citations · 2020

Key Collaborators

Contact & Links