Cooperative gestures for industry: Exploring the efficacy of robot hand configurations in expression of instructional gestures for human–robot interaction

• Published in: The International journal of robotics research 2017-06, Vol.36 (5-7), p.699-720
• Main Authors: Sheikholeslami, Sara, Moon, AJung, Croft, Elizabeth A
• Format: Article
• Language: English
• Subjects: Assembly; Collaboration; Communication; Effectiveness; Effectors; Hand (anatomy); Manipulators; Messages; Recognition; Robot arms; Robotics; Robots; Verbal communication
• ISSN: 0278-3649; 1741-3176
• DOI: 10.1177/0278364917709941

Fast and reliable communication between human worker(s) and robotic assistants is essential for successful collaboration between the agents. This is especially true for typically noisy manufacturing environments that render verbal communication less effective. In this work, we investigate the efficacy of nonverbal communication capabilities of robotic manipulators that have poseable, three-fingered end-effectors (hands). We explore the extent to which different poses of a typical robotic gripper can effectively communicate instructional messages during human–robot collaboration. Within the context of a collaborative car door assembly task, we conducted a series of three studies. We first observed the type of hand configurations that humans use to nonverbally instruct another person (Study 1, N = 17); based on the observation, we examined how well human gestures with frequently used hand configurations are understood by recipients of the message (Study 2, N = 140). Finally, we implemented the most human-recognized human hand configurations on a seven-degree-of-freedom robotic manipulator to investigate the efficacy of having human-inspired hand poses on a robotic hand compared to an unposed hand (Study 3, N = 100). Contributions of this work include presentation of a set of hand configurations humans commonly use to instruct another person in a collaborative assembly scenario, as well as recognition rate and recognition confidence measures for the gestures that humans and robots express using different hand configurations. Results indicate that most gestures are better recognized with a higher level of confidence when displayed with a posed robot hand.