Flattening the Earth, Two Thousand Years of Map Projections

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Handbook Of Human Vibration

The aim of this article is to analyze and review the scientific literature relating to the application of Augmented Reality (AR) technology in industry. AR technology is becoming increasingly diffu...

Augmented reality technology in the manufacturing industry: A review of the last decade

Augmented reality in support of intelligent manufacturing - a systematic literature review

金光雄 著, 「관료와 발전」(서울 : 평민사, 1986)

In this article, the development of an augmented reality–based robotic work cell is presented, consisting of a virtual robot arm, conveyor belt, pallet and computer numerical control machine that s...

Augmented reality–based programming, planning and simulation of a robotic work cell:

With the increasing popularity of virtual reality (VR) technologies, more efforts have been going into developing new input methods. While physical controllers are widely used, more novel techniques, such as eye tracking, are now commercially available. In our work, we investigate the use of physiological signals as input to enhance VR experiences. We present a system using gaze tracking and electromyography on a user’s forearm to make selection tasks in virtual spaces more efficient. In a study with 16 participants, we compared five different input techniques using a Fitts’ law task: Using gaze tracking for cursor movement in combination with forearm contractions for making selections was superior to using an HTC Vive controller, Xbox gamepad, dwelling time, and eye-gaze dwelling time. To explore application scenarios and collect qualitative feedback, we further developed and evaluated a game with our input technique. Our findings inform the design of applications that use eye-gaze tracking and forearm muscle movements for effective user input in VR.

Assessing hands-free interactions for VR using eye gaze and electromyography

With the advancement of Artificial Intelligence technology to make smart devices, understanding how humans develop trust in virtual agents is emerging as a critical research field. Through our research, we report on a novel methodology to investigate user’s trust in auditory assistance in a Virtual Reality (VR) based search task, under both high and low cognitive load and under varying levels of agent accuracy. We collected physiological sensor data such as electroencephalography (EEG), galvanic skin response (GSR), and heart-rate variability (HRV), subjective data through questionnaire such as System Trust Scale (STS), Subjective Mental Effort Questionnaire (SMEQ) and NASA-TLX. We also collected a behavioral measure of trust (congruency of users’ head motion in response to valid/ invalid verbal advice from the agent). Our results indicate that our custom VR environment enables researchers to measure and understand human trust in virtual agents using the matrices, and both cognitive load and agent accuracy play an important role in trust formation. We discuss the implications of the research and directions for future work.

Measuring Human Trust in a Virtual Assistant using Physiological Sensing in Virtual Reality

Navigating in a natural way in augmented reality (AR) and virtual reality (VR) spaces is a large challenge. To this end, we present ArmSwingVR, a locomotion solution for AR/VR spaces that preserves immersion, while being low profile compared to current solutions, particularly walking-in-place (WIP) methods. The user simply needs to swing their arms naturally to navigate in the direction where the arms are swung, without any feet or head movement. The benefits of ArmSwingVR are that arm swinging feels natural for bipedal organisms second only to leg movement, no additional peripherals or sensors are required, it is less obtrusive to swing our arms as opposed to WIP methods, and requires less energy allowing prolong uses for AR/VR. A conducted user study found that our method does not sacrifice immersion while also being more low profile and less energy consumption compared to WIP.

Armswing: using arm swings for accessible and immersive navigation in AR/VR spaces

Human trust is a psycho-physiological state that is difficult to measure, yet is becoming increasingly important for the design of human-computer interactions. This paper explores if human trust can be measured using physiological measures when interacting with a computer interface, and how it correlates with cognitive load. In this work, we present a pilot study in Virtual Reality (VR) that uses a multi-sensory approach of Electroencephalography (EEG), galvanic skin response (GSR), and Heart Rate Variability (HRV) to measure trust with a virtual agent and explore the correlation between trust and cognitive load. The goal of this study is twofold; 1) to determine the relationship between biosignals, or physiological signals with trust and cognitive load, and 2) to introduce a pilot study in VR based on cognitive load level to evaluate trust. Even though we could not report any significant main effect or interaction of cognitive load and trust from the physiological signal, we found that in low cognitive load tasks, EEG alpha band power reflects trustworthiness on the agent. Moreover, cognitive load of the user decreases when the agent is accurate regardless of task’s cognitive load. This could be possible because of small sample size, tasks not stressful enough to induce high cognitive load due to lab study and comfortable environment or timestamp synchronisation error due to fusing data from various physiological sensors with different sample rate.

Yun Suen Pai

Papers

Augmented reality–based programming, planning and simulation of a robotic work cell:

Assessing hands-free interactions for VR using eye gaze and electromyography

Measuring Human Trust in a Virtual Assistant using Physiological Sensing in Virtual Reality

Armswing: using arm swings for accessible and immersive navigation in AR/VR spaces

In AI We Trust: Investigating the Relationship between Biosignals, Trust and Cognitive Load in VR