Haptic Role Allocation and Intention Negotiation in Human-Robot Collaboration

Kucukyilmaz, Ayse

Abstract

This dissertation aims to present a perspective to build more natural shared control systems for physical human-robot cooperation. As the tasks become more complex and more dynamic, many shared control schemes fail to meet the expectation of an effortless interaction that resembles human-human sensory communication. Since such systems are mainly built to improve task performance, the richness of sensory communication is of secondary concern. We suggest that effective cooperation can be achieved when the human’s and the robot’s roles within the task are dynamically updated during the execution of the task. These roles define states for the system, in which the robot’s control leads or follows the human’s actions. In such a system, a state transition can occur at certain times if the robot can determine the user’s intention for gaining/relinquishing control. Specifically, with these state transitions we assign certain roles to the human and the robot. We believe that only by employing the robot with tools to change its behavior during collaboration, we can improve the collaboration experience.

We explore how human-robot cooperation in virtual and physical worlds can be improved using a force-based role-exchange mechanism. Our findings indicate that the proposed role exchange framework is beneficial in a sense that it can improve task performance and the efficiency of the partners during the task, and decrease the energy requirement of the human. Moreover, the results imply that the subjective acceptability of the proposed model is attained only when role exchanges are performed in a smooth and transparent fashion. Finally, we illustrate that adding extra sensory cues on top of a role exchange scheme is useful for improving the sense of interaction during the task, as well as making the system more comfortable and easier to use, and the task more enjoyable.

• Thesis Type: Thesis
• Deposit Date: Feb 26, 2020
• Publicly Available Date: Apr 5, 2020
• Keywords: Robotics, human-computer interfaces, haptics, negotiation, adjustable autonomy
• Public URL: https://nottingham-repository.worktribe.com/output/4040519
• Award Date: Jun 19, 2013