Biblio

Haptic communications and 5G networks in conjunction with AI and robotics will augment the human user experience by enabling real-time task performance via the control of objects remotely. This represents a paradigm shift from content delivery-based networks to task-oriented networks for remote skill set delivery. The transmission of user skill sets in remote task performance marks the advent of a haptic-enabled Internet of Skills (IoS), through which the transmission of touch and actuation sensations will be possible. In this proposed research, a conceptual Task-Technology Fit (TTF) model of a haptic-enabled IoS is developed to link human users and haptic-enabled technologies to technology use and task performance between master (control) and remote (controlled) domains to provide a Quality of Experience (QoE) and Quality of Task (QoT) oriented perspective of a Haptic Internet. Future 5G-enabled applications promise the high availability, security, fast reaction speeds, and reliability characteristics required for the transmission of human user skills over large geographical distances. The 5G network and haptic-enabled IoS considered in this research will support a number of critical applications. One such novel scenario in which a TTF of a Haptic Internet can be modelled is the use case of remote-controlled Unmanned Aerial Vehicles (UAVs). This paper is a contribution towards the realization of a 5G network and haptic-enabled QoE-QoT-centric IoS for augmented user task performance. Future empirical results of this research will be useful to understanding the role that varying degrees of a fit between context-specific task and technology characteristics play in influencing the impact of haptic-enabled technology use for real-time immersive remote UAV (drone) control task performance.

Human actuation is the idea of using people to provide large-scale force feedback to users. The Haptic Turk system, for example, used four human actuators to lift and push a virtual reality user; TurkDeck used ten human actuators to place and animate props for a single user. While the experience of human actuators was decent, it was still inferior to the experience these people could have had, had they participated as a user. In this paper, we address this issue by making everyone a user. We introduce mutual human actuation, a version of human actuation that works without dedicated human actuators. The key idea is to run pairs of users at the same time and have them provide human actuation to each other. Our system, Mutual Turk, achieves this by (1) offering shared props through which users can exchange forces while obscuring the fact that there is a human on the other side, and (2) synchronizing the two users' timelines such that their way of manipulating the shared props is consistent across both virtual worlds. We demonstrate mutual human actuation with an example experience in which users pilot kites though storms, tug fish out of ponds, are pummeled by hail, battle monsters, hop across chasms, push loaded carts, and ride in moving vehicles.