Research Recommendations from the Airplane Simulation Transfer Literature

This descriptive review aims to identify research gaps in the airplane, simulation transfer of training literature. The research question is: What are the recommendations for future research from the simulation experiments using a true transfer or a quasi-transfer design to study the near or far transfer of airplane flying knowledge, skills, or abilities among adults? The method involves an exhaustive survey of English-language, peer-reviewed publications available online. The results include eight seminal reviews of the aviation literature published since 1973, 26 empirical studies published since 2004, and four general reviews to situate the aviation literature. The primary transfer studies encompass four themes: training proficiency, motion, abnormal events, and control tasks. This review addresses current research needs by presenting summaries and recommendations from the transfer literature, identifying gaps, and proposing an agenda for future research. It serves to inform researchers, practitioners, manufacturers, and regulators in the field of flight simulation training

An Augmented Interaction Strategy For Designing Human-Machine Interfaces For Hydraulic Excavators

Lack of adequate information feedback and work visibility, and fatigue due to repetition have been identified as the major usability gaps in the human-machine interface (HMI) design of modern hydraulic excavators that subject operators to undue mental and physical workload, resulting in poor performance. To address these gaps, this work proposed an innovative interaction strategy, termed “augmented interaction”, for enhancing the usability of the hydraulic excavator. Augmented interaction involves the embodiment of heads-up display and coordinated control schemes into an efficient, effective and safe HMI. Augmented interaction was demonstrated using a framework consisting of three phases: Design, Implementation/Visualization, and Evaluation (D.IV.E). Guided by this framework, two alternative HMI design concepts (Design A: featuring heads-up display and coordinated control; and Design B: featuring heads-up display and joystick controls) in addition to the existing HMI design (Design C: featuring monitor display and joystick controls) were prototyped. A mixed reality seating buck simulator, named the Hydraulic Excavator Augmented Reality Simulator (H.E.A.R.S), was used to implement the designs and simulate a work environment along with a rock excavation task scenario. A usability evaluation was conducted with twenty participants to characterize the impact of the new HMI types using quantitative (task completion time, TCT; and operating error, OER) and qualitative (subjective workload and user preference) metrics. The results indicated that participants had a shorter TCT with Design A. For OER, there was a lower error probability due to collisions (PER1) with Design A, and lower error probability due to misses (PER2)with Design B. The subjective measures showed a lower overall workload and a high preference for Design B. It was concluded that augmented interaction provides a viable solution for enhancing the usability of the HMI of a hydraulic excavator

Robotic simulators for tissue examination training with multimodal sensory feedback

Tissue examination by hand remains an essential technique in clinical practice. The effective application depends on skills in sensorimotor coordination, mainly involving haptic, visual, and auditory feedback. The skills clinicians have to learn can be as subtle as regulating finger pressure with breathing, choosing palpation action, monitoring involuntary facial and vocal expressions in response to palpation, and using pain expressions both as a source of information and as a constraint on physical examination. Patient simulators can provide a safe learning platform to novice physicians before trying real patients. This paper reviews state-of-the-art medical simulators for the training for the first time with a consideration of providing multimodal feedback to learn as many manual examination techniques as possible. The study summarizes current advances in tissue examination training devices simulating different medical conditions and providing different types of feedback modalities. Opportunities with the development of pain expression, tissue modeling, actuation, and sensing are also analyzed to support the future design of effective tissue examination simulators

Multimodal Human-Machine Interface For Haptic-Controlled Excavators

The goal of this research is to develop a human-excavator interface for the hapticcontrolled excavator that makes use of the multiple human sensing modalities (visual, auditory haptic), and efficiently integrates these modalities to ensure intuitive, efficient interface that is easy to learn and use, and is responsive to operator commands. Two empirical studies were conducted to investigate conflict in the haptic-controlled excavator interface and identify the level of force feedback for best operator performance

Effects of Motion Cues on the Training of Multi-Axis Manual Control Skills

The study described in this paper investigated the effects of two different hexapod motion configurations on the training and transfer of training of a simultaneous roll and pitch control task. Pilots were divided between two groups which trained either under a baseline hexapod motion condition, with motion typically provided by current training simulators, or an optimized hexapod motion condition, with increased fidelity of the motion cues most relevant for the task. All pilots transferred to the same full-motion condition, representing motion experienced in flight. A cybernetic approach was used that gave insights into the development of pilots use of visual and motion cues over the course of training and after transfer. Based on the current results, neither of the hexapod motion conditions can unambiguously be chosen as providing the best motion for training and transfer of training of the used multi-axis control task. However, the optimized hexapod motion condition did allow pilots to generate less visual lead, control with higher gains, and have better disturbance-rejection performance at the end of the training session compared to the baseline hexapod motion condition. Significant adaptations in control behavior still occurred in the transfer phase under the full-motion condition for both groups. Pilots behaved less linearly compared to previous single-axis control-task experiments; however, this did not result in smaller motion or learning effects. Motion and learning effects were more pronounced in pitch compared to roll. Finally, valuable lessons were learned that allow us to improve the adopted approach for future transfer-of-training studies

Effects of False Tilt Cues on the Training of Manual Roll Control Skills

This paper describes a transfer-of-training study performed in the NASA Ames Vertica lMotion Simulator. The purpose of the study was to investigate the effect of false tilt cues on training and transfer of training of manual roll control skills. Of specific interest were the skills needed to control unstable roll dynamics of a mid-size transport aircraft close to the stall point. Nineteen general aviation pilots trained on a roll control task with one of three motion conditions: no motion, roll motion only, or reduced coordinated roll motion. All pilots transferred to full coordinated roll motion in the transfer session. A novel multimodal pilot model identification technique was successfully applied to characterize how pilots' use of visual and motion cues changed over the course of training and after transfer. Pilots who trained with uncoordinated roll motion had significantly higher performance during training and after transfer, even though they experienced the false tilt cues. Furthermore, pilot control behavior significantly changed during the two sessions, as indicated by increasing visual and motion gains, and decreasing lead time constants. Pilots training without motion showed higher learning rates after transfer to the full coordinated roll motion case

An Overview of Self-Adaptive Technologies Within Virtual Reality Training

This overview presents the current state-of-the-art of self-adaptive technologies within virtual reality (VR) training. Virtual reality training and assessment is increasingly used for five key areas: medical, industrial & commercial training, serious games, rehabilitation and remote training such as Massive Open Online Courses (MOOCs). Adaptation can be applied to five core technologies of VR including haptic devices, stereo graphics, adaptive content, assessment and autonomous agents. Automation of VR training can contribute to automation of actual procedures including remote and robotic assisted surgery which reduces injury and improves accuracy of the procedure. Automated haptic interaction can enable tele-presence and virtual artefact tactile interaction from either remote or simulated environments. Automation, machine learning and data driven features play an important role in providing trainee-specific individual adaptive training content. Data from trainee assessment can form an input to autonomous systems for customised training and automated difficulty levels to match individual requirements. Self-adaptive technology has been developed previously within individual technologies of VR training. One of the conclusions of this research is that while it does not exist, an enhanced portable framework is needed and it would be beneficial to combine automation of core technologies, producing a reusable automation framework for VR training

A Novel Haptic Simulator for Evaluating and Training Salient Force-Based Skills for Laparoscopic Surgery

Laparoscopic surgery has evolved from an \u27alternative\u27 surgical technique to currently being considered as a mainstream surgical technique. However, learning this complex technique holds unique challenges to novice surgeons due to their \u27distance\u27 from the surgical site. One of the main challenges in acquiring laparoscopic skills is the acquisition of force-based or haptic skills. The neglect of popular training methods (e.g., the Fundamentals of Laparoscopic Surgery, i.e. FLS, curriculum) in addressing this aspect of skills training has led many medical skills professionals to research new, efficient methods for haptic skills training. The overarching goal of this research was to demonstrate that a set of simple, simulator-based haptic exercises can be developed and used to train users for skilled application of forces with surgical tools. A set of salient or core haptic skills that underlie proficient laparoscopic surgery were identified, based on published time-motion studies. Low-cost, computer-based haptic training simulators were prototyped to simulate each of the identified salient haptic skills. All simulators were tested for construct validity by comparing surgeons\u27 performance on the simulators with the performance of novices with no previous laparoscopic experience. An integrated, \u27core haptic skills\u27 simulator capable of rendering the three validated haptic skills was built. To examine the efficacy of this novel salient haptic skills training simulator, novice participants were tested for training improvements in a detailed study. Results from the study demonstrated that simulator training enabled users to significantly improve force application for all three haptic tasks. Research outcomes from this project could greatly influence surgical skills simulator design, resulting in more efficient training

Magician simulator — A realistic simulator for heterogeneous teams of autonomous robots

We report on the development of a new simulation environment for use in Multi-Robot Learning, Swarm Robotics, Robot Teaming, Human Factors and Operator Training. The simulator provides a realistic environment for examining methods for localization and navigation, sensor analysis, object identification and tracking, as well as strategy development, interface refinement and operator training (based on various degrees of heterogeneity, robot teaming, and connectivity). The simulation additionally incorporates real-time human-robot interaction and allows hybrid operation with a mix of simulated and real robots and sensor inputs