This paper concerns human-inspired robotic eye-hand coordination algorithms using custom built robotic eyes that were interfaced with a Baxter robot. Eye movement was programmed anthropomorphically based on previously reported research on human eye-hand coordination during grasped object transportation. Robotic eye tests were first performed on a component level where accurate position and temporal control were achieved. Next, 11 human subjects were recruited to observe the novel robotic system to quantify the ability of robotic eye-hand coordination algorithms to convey two kinds of information to people during object transportation tasks: first, the transported object’s delivery location and second, the level of care exerted by the robot to transport the object. Most subjects correlated decreased frequency in gaze fixations on an object’s target location with increased care of transporting an object, although these results were somewhat mixed among the 11 human subjects. Additionally, the human subjects were able to reliably infer the delivery location of the transported object purely by the robotic eye-hand coordination algorithm with an overall success rate of 91.4%. These results suggest that anthropomorphic eye-hand coordination of robotic entities could be useful in pedagogical or industrial settings.

本文涉及使用与 Baxter 机器人交互的定制机器人眼睛的受人类启发的机器人手眼协调算法。根据先前报道的关于在抓取物体运输过程中人眼手协调的研究，对眼球运动进行拟人化编程。机器人眼睛测试首先在实现精确位置和时间控制的组件级别上进行。接下来，招募了 11 名人类受试者来观察新的机器人系统，以量化机器人眼手协调算法在物体运输任务中向人们传达两种信息的能力：一是运输物体的交付位置，二是运输物体的水平。机器人在运输物体时所采取的谨慎措施。大多数受试者将注视对象目标位置的注视频率降低与运输对象的注意增加相关，尽管这些结果在 11 名人类受试者中有些混杂。此外，人类受试者能够仅通过机器人眼手协调算法可靠地推断运输物体的交付位置，总体成功率为 91.4%。这些结果表明，机器人实体的拟人化眼手协调可能在教学或工业环境中有用。人类受试者完全通过机器人眼手协调算法能够可靠地推断出运输物体的交付位置，总体成功率为91.4%。这些结果表明，机器人实体的拟人化眼手协调可能在教学或工业环境中有用。人类受试者完全通过机器人眼手协调算法能够可靠地推断出运输物体的交付位置，总体成功率为91.4%。这些结果表明，机器人实体的拟人化眼手协调可能在教学或工业环境中有用。