Carolina Cani

About

Carolina Cani is a leading researcher in the field of human-robot collaboration, with a primary focus on enhancing safety through intelligent systems. Her work bridges the gap between robotics and artificial intelligence, particularly in developing deep and machine learning techniques to prevent collisions and ensure secure interactions between humans and robots. In her highly cited 2021 study, "Modeling and assessing an intelligent system for safety in human-robot collaboration using deep and machine learning techniques," she introduced a novel framework that models and evaluates safety protocols, earning 15 citations for its practical implications. Another key contribution, "A New Mechanism for Collision Detection in Human–Robot Collaboration using Deep Learning Techniques," has garnered 13 citations, showcasing her ability to create innovative, real-time detection systems. Cani’s research is pivotal for advancing collaborative robotics in manufacturing and service industries, where safe coexistence is critical. Her work not only addresses immediate safety challenges but also sets a foundation for future autonomous systems. With a growing citation impact, Cani is recognized as a rising voice in intelligent robotics, inspiring safer, more efficient human-robot partnerships.

Research Focus

Key Achievements

Top Papers

1. 1
   Modeling and assessing an intelligent system for safety in human-robot collaboration using deep and machine learning techniques

   15 citations · 2021
2. 2
   A New Mechanism for Collision Detection in Human–Robot Collaboration using Deep Learning Techniques

   13 citations · 2021

Key Collaborators

Contact & Links