The role of the research simulator in the systems development of rotorcraft

The potential application of the research simulator to future rotorcraft systems design, development, product improvement evaluations, and safety analysis is examined. Current simulation capabilities for fixed-wing aircraft are reviewed and the requirements of a rotorcraft simulator are defined. The visual system components, vertical motion simulator, cab, and computation system for a research simulator under development are described

Effects of Transparency and Haze on Trust and Performance During a Full Motion Video Analysis Task

Automation is pervasive across all task domains, but its adoption poses unique challenges within the intelligence, surveillance, and reconnaissance (ISR) domain. When users are unable to establish optimal levels of trust in the automation, task accuracy, speed, and automation usage suffer (Chung & Wark, 2016). Degraded visual environments (DVEs) are a particular problem in ISR; however, their specific effects on trust and task performance are still open to investigation (Narayanaswami, Gandhe, & Mehra, 2010). Research suggests that transparency of automation is necessary for users to accurately calibrate trust levels (Lyons et al., 2017). Chen et al. (2014) proposed three levels of transparency, with varying amounts of information provided to the user at each level. Transparency may reduce the negative effects of DVEs on trust and performance, but the optimal level of transparency has not been established (Nicolau & McKnight, 2006). The current study investigated the effects of varying levels of transparency and image haze on task performance and user trust in automation. A new model predicting trust from attention was also proposed. A secondary aim was to investigate the usefulness of task shedding and accuracy as measures of trust. A group of 48 undergraduates attempted to identify explosive emplacement activity within a series of full motion video (FMV) clips, aided by an automated analyst. The experimental setup was intended to replicate Level 5 automation (Sheridan & Verplank, 1978). Reliability of the automated analyst was primed to participants as 78% historical accuracy. For each clip, participants could shed their decision to an automated analyst. Higher transparency of automation predicted significantly higher accuracy, whereas hazy visual stimuli predicted significantly lower accuracy and 2.24 times greater likelihood of task shedding. Trust significantly predicted accuracy, but not task shedding. Participants were fastest in the medium transparency condition. The proposed model of attention was not supported; however, participants’ scanning behavior differed significantly between hazy and zero haze conditions. The study was limited by task complexity due to efforts to replicate real-world conditions, leading to confusion on the part of some participants. Results suggested that transparency of automation is critical, and should include purpose, process, performance, reason, algorithm, and environment information. Additional research is needed to explain task shedding behavior and to investigate the relationship between degrade visual environments, transparency of automation, and trust in automation

Visibility in underwater robotics: Benchmarking and single image dehazing

Dealing with underwater visibility is one of the most important challenges in autonomous underwater robotics. The light transmission in the water medium degrades images making the interpretation of the scene difficult and consequently compromising the whole intervention. This thesis contributes by analysing the impact of the underwater image degradation in commonly used vision algorithms through benchmarking. An online framework for underwater research that makes possible to analyse results under different conditions is presented. Finally, motivated by the results of experimentation with the developed framework, a deep learning solution is proposed capable of dehazing a degraded image in real time restoring the original colors of the image.Una de las dificultades más grandes de la robótica autónoma submarina es lidiar con la falta de visibilidad en imágenes submarinas. La transmisión de la luz en el agua degrada las imágenes dificultando el reconocimiento de objetos y en consecuencia la intervención. Ésta tesis se centra en el análisis del impacto de la degradación de las imágenes submarinas en algoritmos de visión a través de benchmarking, desarrollando un entorno de trabajo en la nube que permite analizar los resultados bajo diferentes condiciones. Teniendo en cuenta los resultados obtenidos con este entorno, se proponen métodos basados en técnicas de aprendizaje profundo para mitigar el impacto de la degradación de las imágenes en tiempo real introduciendo un paso previo que permita recuperar los colores originales

The assessment of visual behaviour and depth perception in surgery

Imperial Users onl

Immersive 360° video for forensic education

Throughout the globe, training in the investigation of forensic crime scene work is a vital part of the overall training process within Police Academies and forensic programs throughout the world. However, the exposure of trainee forensic officers to real life scenes, by instructors, is minimal due to the delicate nature of information presented within them and the overall difficulty of Forensic investigations. Virtual Reality (VR) is computer technology utilising headsets, to produce lifelike imageries, sounds and perceptions simulating physical presence inside a virtual setting to a user. The user is able to look around the virtual world and often interact with virtual landscapes or objects. VR headsets are head‐mounted goggles with a screen in front of the eyes (Burdea & Coffet 2003). The use of VR varies widely from personal gaming to classroom learning. Uses also include computerised tools that are used solely online. The current use of VR within Forensic Science is that it is used widely in several capacities that include the training and examination of new forensic officers. However, there is minimal review and authentication of the efficiency of VR use for the teaching of forensic investigation. This is surprising, as the VR field has experienced rapid expansion in the educating of many varying fields over the past few years. Even though VR could enhance forensic training by offering another, perhaps more versatile, engaging way of learning, no devoted VR application has yet been commercially implemented for forensic examination education. Research into VR is a fairly young field, however the technology and use of it is still rapidly growing and the improvement of interactive tools is inevitably having an impact on all facets of learning and teaching

Eye-tracking assistive technologies for individuals with amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis, also known as ALS, is a progressive nervous system disorder that affects nerve cells in the brain and spinal cord, resulting in the loss of muscle control. For individuals with ALS, where mobility is limited to the movement of the eyes, the use of eye-tracking-based applications can be applied to achieve some basic tasks with certain digital interfaces. This paper presents a review of existing eye-tracking software and hardware through which eye-tracking their application is sketched as an assistive technology to cope with ALS. Eye-tracking also provides a suitable alternative as control of game elements. Furthermore, artificial intelligence has been utilized to improve eye-tracking technology with significant improvement in calibration and accuracy. Gaps in literature are highlighted in the study to offer a direction for future research

Enhancing depth cues with AR visualization for forklift operation assistance in warehouse.

With warehouse operations contributing to the major part of logistics, architects tend to utilize every inch of the space allocated to maximize the stacking space. Increasing the height of the aisles and narrowing down the aisle-aisle space are major design issues in doing so. Even though forklift manufacturing companies introduced high reach trucks and forklifts for narrow aisles, forklift operators face many issues while working with heavy pallets. This thesis focused on developing a systemthat uses Augmented Reality(AR) to aid forklift operators in performing their pallet racking and pick up tasks. It used AR technology to superimpose virtual cues over the real world specifying the pallets to be picked up and moved and also assist in operating the forklift using depth cues. This aims to increase the productivity of the forklift operators in the warehouse. Depth cues are overlaid on a live video feed from a camera attached to the front of the forklift which was displayed using a laptop to the participants. To evaluate the usability of the system designed, an experiment was conducted and the performance results and the feedback from the participants was evaluated. A remote controlled toy forklift was used to conduct the experiment and a motion tracking system was set-up to track the cab and pallet. Simple pallet handling tasks were designed for the participants and their performance and feedback was collected and analysed. This thesis shows how AR offers a simple and effecient solution for the problems faced by forklift operators while performing pallet handling tasks in warehouse