Gioel Asuni

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 st...

This paper presents a self-organizing neural network model for visuo-motor coordination of a redundant humanoid robot arm in reaching tasks. The proposed approach is based on a biologically-inspired model which replicates some characteristics of human control: learning occurs through an action-perception cycle and does not requires explicit knowled...

Introduction Biological Framework of Motor Control Modeling and Robotic Approaches Structure and Functionality of Proposed Neural Model Experimental Results Conclusion Acknowledgments References

This paper presents a neural model for visuo-motor coordination of a redundant robotic manipulator in reaching tasks. The model was developed for, and experimentally validated on, a neurobotic platform for manipulation. The proposed approach is based on a biologically-inspired model, which replicates the human brain capability of creating associati...

This paper presents the application of a neural approach in the control of a 7-DOF robotic head. The inverse kinematics problem is addressed, for the control of the gaze fixation point of two cameras mounted on the robotic head. The proposed approach is based on a biologically-inspired model, which replicates the human brain capability of creating...

This paper describes an experimental work conducted in order to estimate the conditions of applicability of expected perception (EP) based on a scheme for robot sensorimotor coordination. The starting hypothesis is that predictions of incoming sensory data can improve sensorymotor coordination respect to pure feedback loops. This implies that the e...

This paper presents a novel scheme for sensor-based control of robotics manipulators by means of artificial neural networks. The system is able to control simple reaching tasks by only fusing visual and proprioceptive sensory data, without computational kinematic modeling of the arm structure, Thanks to the generalization features typical of the ne...

We present a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach for and to grasp an object, while pre-shaping the fingers to the required grasp configuration. A model for sensory-motor coordination derived from studies in humans inspired the development of the scheme. A special fe...