A bio-inspired predictive sensory-motor coordination scheme for robot reaching and preshaping

• Published in: Autonomous robots 2008-08, Vol.25 (1-2), p.85-101
• Main Authors: Laschi, Cecilia, Asuni, Gioel, Guglielmelli, Eugenio, Teti, Giancarlo, Johansson, Roland, Konosu, Hitoshi, Wasik, Zbigniew, Carrozza, Maria Chiara, Dario, Paolo
• Format: Article
• Language: English
• Subjects: Artificial Intelligence; Artificial neural networks; Autonomous; Computer Imaging; Configurations; Control; Coordination; End effectors; Engineering; expected perception; Feedback; Fuzzy logic; Grasping; Grasping (robotics); Humanoid; internal models; Mathematical models; Mechatronics; Motor ability; neuro-fuzzy controllers; Pattern Recognition and Graphics; Predictions; Predictive control; Robot control; robot grasping; robot learning; Robotics; Robotics and Automation; Robots; Sensory feedback; sensory-motor coordination; Tactile; Vision
• ISSN: 0929-5593; 1573-7527; 1573-7527
• DOI: 10.1007/s10514-007-9065-4

This paper presents a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach an object while pre-shaping the fingers to the required grasp configuration and while predicting the tactile image that will be perceived after grasping. A model for sensory-motor coordination derived from studies in humans inspired the development of this scheme. A peculiar feature of this model is the prediction of the tactile image. The implementation of the proposed scheme is based on a neuro-fuzzy module that, after a learning phase, starting from visual data, calculates the position and orientation of the hand for reaching, selects the best-suited hand configuration, and predicts the tactile feedback. The implementation of the scheme on a humanoid robot allowed experimental validation of its effectiveness in robotics and provided perspectives on applications of sensory predictions in robot motor control.