To ensure collision avoidance in flocking, a critical approach consists of decomposing the overall problem into a series of subtasks, with each stage progressively increasing the complexity of subtasks to be addressed. TSCAL performs online learning and offline transfer in an alternating and iterative fashion. On-the-fly immunoassay To address online learning needs, we propose a hierarchical recurrent attention multi-agent actor-critic (HRAMA) algorithm to determine the policies required for the corresponding subtasks in each learning stage. Offline knowledge exchange between adjacent processing stages is accomplished by means of two strategies: model reload and buffer reuse. Through numerical simulations, we ascertain the significant advantages of TSCAL in policy optimization, sample efficiency, and the stability of the learning process. In conclusion, the high-fidelity hardware-in-the-loop (HITL) simulation procedure is utilized to assess TSCAL's adaptability. A video showcasing the processes of numerical and HITL simulations is located at the following website: https//youtu.be/R9yLJNYRIqY.
The existing metric-based few-shot classification method is prone to error due to the misinterpretation of task-unrelated objects or backgrounds; the limited support set samples fail to adequately distinguish the task-related targets. The ability of humans to focus solely on the task-relevant elements within support images, thereby avoiding distractions from irrelevant details, is a key component of wisdom in few-shot classification tasks. Therefore, we suggest explicitly learning task-relevant saliency features, which will be incorporated into the metric-based few-shot learning framework. The task is organized into three phases, which are modeling, analyzing, and matching. During the modeling stage, a saliency-sensitive module (SSM) is integrated, serving as an inexact supervision task concurrently trained with a conventional multi-class classification undertaking. The efficacy of SSM is demonstrated by its ability to enhance the fine-grained representation of feature embedding and to identify task-relevant salient features. We concurrently propose a task-related saliency network (TRSN), a lightweight self-training network, to extract task-specific saliency from the output of the SSM model. The analytical procedure mandates the fixing of TRSN, using it thereafter for novel task handling. TRSN meticulously extracts task-relevant features, whilst minimizing the influence of irrelevant ones. We accomplish accurate sample discrimination during the matching stage by enhancing the task-specific features. Evaluation of the proposed approach involves extensive experimentation across five-way, 1-shot, and 5-shot configurations. Our methodology persistently outperforms benchmarks, demonstrating consistent progress and achieving state-of-the-art results.
Using a Meta Quest 2 VR headset equipped with eye-tracking technology, we introduce a necessary baseline for evaluating eye-tracking interactions in this study, conducted with 30 participants. Participants navigated 1098 targets under various AR/VR-inspired conditions, encompassing both conventional and modern targeting and selection methods. With an eye-tracking system capable of approximately 90Hz refresh rate and sub-1-degree mean accuracy errors, we use circular white world-locked targets for our measurements. Our designed comparison, in a button-pressing targeting exercise, involved unadjusted, cursorless eye tracking versus controller and head-tracking systems, both employing cursors. Throughout all inputs, the positioning of targets followed a design similar to the ISO 9241-9 reciprocal selection task format, and an alternative format with targets more uniformly dispersed near the center. Targets, laid out flat on a plane or touching a sphere, were rotated to face the user. Our initial intent was for a fundamental investigation, but unmodified eye-tracking, with no cursor or feedback, dramatically surpassed head-tracking by 279% and showcased comparable throughput with the controller, a remarkable 563% improvement. Eye-tracking technology demonstrably enhanced user assessments of ease of use, adoption, and fatigue compared to head-mounted devices, achieving enhancements of 664%, 898%, and 1161%, respectively. Similarly, eye-tracking yielded ratings comparable to those of controllers, resulting in reductions of 42%, 89%, and 52% respectively. The percentage of misses in eye tracking (173%) was considerably greater than the corresponding rates for controller (47%) and head (72%) tracking. This baseline study's collective findings strongly suggest that eye tracking, even with minor sensible interaction design adjustments, holds significant potential to transform interactions within next-generation AR/VR head-mounted displays.
Two effective strategies for virtual reality locomotion interfaces are omnidirectional treadmills (ODTs) and redirected walking (RDW). All types of devices can integrate through ODT, a mechanism that fully compresses the physical space. The user experience within ODT experiences disparities in different directions, yet the premise of interaction between users and integrated devices establishes a satisfying correspondence between the virtual and physical realms. RDW technology relies on visual indicators to precisely locate the user within the physical environment. The principle of incorporating RDW technology into ODT, directing users with visual cues, leads to a more satisfying user experience and optimal utilization of ODT's integrated devices. This paper analyzes the transformative prospects of merging RDW technology with ODT, and formally proposes the concept of O-RDW (ODT-driven RDW). Two baseline algorithms, OS2MD (ODT-based steer to multi-direction) and OS2MT (ODT-based steer to multi-target), are introduced, uniting the strengths of RDW and ODT. Employing a simulation environment, this paper undertakes a quantitative examination of the diverse scenarios where the two algorithms prove applicable, and how various crucial elements affect their performance metrics. Practical application of multi-target haptic feedback showcases the successful deployment of the two O-RDW algorithms, as substantiated by the simulation experiments' findings. O-RDW technology's practicality and effectiveness in actual deployment are further substantiated by the findings of the user study.
For the precise presentation of mutual occlusion between virtual and physical objects in augmented reality (AR), the occlusion-capable optical see-through head-mounted display (OC-OSTHMD) is being actively developed in current years. Nevertheless, the application of occlusion using specialized OSTHMDs hinders the widespread use of this attractive feature. For common OSTHMDs, a novel approach for achieving mutual occlusion is suggested in this paper. BAY613606 A wearable device, enabling per-pixel occlusion, has been designed and produced. Occlusion capability is added to OSTHMD devices by connecting them before the optical combiners. A HoloLens 1 prototype was constructed. The demonstration of the virtual display's mutual occlusion is performed in real time. A color correction algorithm is formulated to address the color aberration problem caused by the occlusion device. Examples of potential applications, such as replacing the texture of actual objects and showcasing more lifelike semi-transparent objects, are presented. The proposed system's application in augmented reality is anticipated to achieve a universal implementation of mutual occlusion.
A cutting-edge Virtual Reality (VR) headset must offer a display with retina-level resolution, a wide field of view (FOV), and a high refresh rate, transporting users to an intensely immersive virtual realm. Nevertheless, the manufacturing of such high-caliber displays, alongside real-time rendering and the task of data transfer, presents significant hurdles. In order to resolve this matter, we present a dual-mode virtual reality system that leverages the spatio-temporal characteristics of human visual perception. A novel optical architecture is implemented in the proposed VR system. To achieve the best visual perception, the display modifies its display modes in response to the user's needs across different display scenarios, adapting spatial and temporal resolution based on the allocated display budget. A detailed design pipeline for the dual-mode VR optical system is introduced in this work, coupled with the construction of a bench-top prototype, using only off-the-shelf hardware and components to confirm its ability. Our proposed VR approach, when compared to standard systems, showcases enhanced efficiency and flexibility in allocating display resources. This research anticipates fostering the development of VR devices aligned with human visual capabilities.
A plethora of studies demonstrate the critical role of the Proteus effect within advanced virtual reality deployments. medial superior temporal Expanding on prior research, this study examines the harmonious relationship (congruence) between self-embodiment (avatar) and the virtual environment. We investigated how avatar and environmental types, and their compatibility, affected the perceived authenticity of the avatar, the sense of being the avatar, spatial presence, and the Proteus effect's demonstration. In a 22-participant between-subjects experiment, participants physically represented themselves with an avatar (either in sports apparel or business attire) during light exercises in a virtual reality setting, with the environment matching or mismatching the avatar's theme. A significant connection between the avatar and its surrounding environment greatly affected the plausibility of the avatar, though it had no impact on the user's sense of embodiment or spatial awareness. However, a substantial Proteus effect appeared solely for participants who reported a strong feeling of (virtual) body ownership, suggesting a critical role for a profound sense of owning a virtual body in the activation of the Proteus effect. We interpret the results, employing established bottom-up and top-down theories of the Proteus effect, thus contributing to a more nuanced understanding of its underlying mechanisms and determinants.