Gaze Control, Motor Skill, and Prediction

生物视觉系统采用协同凝视控制来获取、固定和稳定图像。这笔拨款将帮助罗彻斯特大学的一个实验机器人开发类似的目光控制能力。一项初步研究模拟了这些机制，用于快速注视转移、目标跟踪、头部运动的眼睛补偿以及立体摄像机对目标的逼近。这项新工作将实现、验证和扩展用于主动机器人系统的控制算法。

Biological vision systems employ cooperating gaze controls to acquire, fixate, and stabilize images. This grant will help develop similar gaze-control capabilities for an experimental robot head at the University of Rochester. A pilot study has simulated these mechanisms for fast gaze shifts, target tracking, eye compensation for head motion, and verging of stereo cameras on a target. The new work will implement, validate, and extend the control algorithms for use in active robotic systems.