Antonina Starita

About

Antonina Starita is a pioneering researcher in biologically inspired robotics and neural control systems, with a focus on bridging the gap between biological motor control and robotic manipulation. Her work centers on developing neuro-controllers that enable robots to autonomously learn visuomotor coordination, mimicking the human brain's ability to fuse sensory data—such as vision and proprioception—without relying on explicit kinematic models. Starita's key contributions include a groundbreaking approach to robotic grasping that allows systems to autonomously discover relationships between perceptual inputs and motor actions, a critical step toward adaptive robotics in dynamic environments. She also advanced medical robotics with an adaptive segmentation algorithm for micro-endoscopic navigation within the human spinal cord, enhancing safety and precision in robot-assisted surgery. Her most cited paper, "Implementing robotic grasping tasks using a biological approach" (20 citations), underscores her impact in the field, while her work on neural models for visuomotor coordination (7 citations) has influenced subsequent research in anthropomorphic arm control. Starita's integration of biological principles into robotic systems continues to inspire innovations in autonomous manipulation and medical robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Implementing robotic grasping tasks using a biological approach

   20 citations · 2002
2. 2
   A segmentation algorithm for a robotic micro-endoscope for exploration of the spinal cord

   8 citations · 2004
3. 3
   A neuro-controller for robotic manipulators based on biologically-inspired visuo-motor co-ordination neural models

   7 citations · 2003
4. 4
   Neurocontroller for Robot Arms Based on Biologically Inspired Visuomotor Coordination Neural Models

   3 citations · 2006
5. 5
   A RLWPR network for learning the internal model of an anthropomorphic robot arm

   2 citations · 2005

Key Collaborators

Contact & Links