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This SIGGRAPH 2026 Frontiers workshop discusses Flying Light Specks (FLSs), their application use cases, current status, and future research directions. An FLS is a miniature drone equipped with a lighting apparatus. It is a building block of next-generation displays, ranging from desktop Dronevision (DV) systems to room-sized holodecks and outdoor spatial-computing environments. Swarms of FLSs will illuminate graphics and animations visible to the naked eye, allowing users to interact with them using their bare hands. This workshop describes the emerging technology behind this exciting area of research. Topics include a classification of FLS devices with LightBender and its 2D lighting apparatus as an example, an end-to-end architecture from content generation to illumination and interaction, physicalization of virtual objects for bare-hand interaction, and a monitoring environment to evaluate and refine the quality of user experience while ensuring their safety. This visionary workshop articulates how these technologies will be used to realize DVs, holodecks, and spatial computing. It describes the use of complementary technologies that realize the vision of these systems. An example is HoloTiles by Lanny Smoot, SIGGRAPH 2026 keynote speaker, as the flooring of a holodeck. More generally, we examine robots of varying forms, morphologies, and functions in relation to DV, holodecks, and spatial computing. This workshop is the prelude to the Third International Conference on Holodecks that takes place on the campus of the University of Southern California on July 24, 2026. The conference includes a tour of our Fly lab with hands-on experience using our authoring tools, FLSs, and illuminations. 

This companion paper provides artifacts and instructions on replicating the experiments in the ACM Multimedia 2024 paper entitled "Swarical: An Integrated Hierarchical Approach to Localizing Flying Light Specks." Swarm-based hierarchical, Swarical, is a localization technique that enables miniature drones, Flying Light Specks (FLSs), to accurately and efficiently localize and illuminate complex 2D and 3D shapes. It consists of two components, an offline planner and an online localization technique that executes on an FLS. The offline planner uses the FLS sensor specification for positioning to convert mesh files into swarms of FLSs. Some FLSs are dark and used only for localization. We reported the online localization technique to be fast and highly accurate. We describe how to reproduce this finding using our artifacts. 

This paper presents the design and implementation of a Flying Light Speck (FLS) to illuminate English letters. The FLS uses its onboard camera and computing to localize and follow a trajectory to illuminate a letter. We evaluate the illuminations quantitatively and qualitatively. The latter is based on an IRB approved human subject study with 20 participants. The obtained results show a 42 to 56 millimeter error that impacts the detection of letters. A key finding is that the order in which the illumination of letters is presented to subjects has a significant effect on detection duration. 

Authoring tools typically convert 3D animation data into 2D rasterized formats for display, a process that imposes computational burdens, degrades depth fidelity, and complicates the recovery of original 3D information. This paper presents the first known direct integration of Blender, a widely used 3D animation tool, with Dronevision (DV), a 3D multimedia display composed of synchronized Flying Light Specks (FLSs). In addition to raster-based pipelines, this integration enables real-time, high-fidelity illumination of 3D animations directly in physical space. Our system leverages Blender’s piecewise animation model—comprising manually placed keyframes and mathematically defined interpolation functions—to generate spatiotemporal trajectories that are mapped to the motion of autonomous FLS drones. We introduce the concept of a display clock that is maintained by each FLS and synchronized across all FLSs using a broadcast based protocol. Our techniques have a fixed complexity independent of the number of FLSs. They enable a DV to scale to millions and billions of FLSs. 

We present CrazyJoystick, a flyable handheld joystick allowing seamless interaction methods to change between joystick and hand-tracking while displaying on-demand haptic feedback in extended reality (XR). Our system comprises a quadrotor that can autonomously approach the user when needed, addressing the limitations of conventional handheld and wearable devices that require continuous carrying throughout interactions. CrazyJoystick dynamically reallocates all thrust for haptic rendering during stationary states, eliminating the need to hover while delivering feedback. A customized cage allows users to grasp the device and interact with virtual objects, receiving 3.5 degree-of-freedom feedback. This novel transition method allows us to harvest the aerial mobility from multi-rotor based haptic devices, while having high force-to-weight ratios from being handheld during interaction. This paper describes the design and implementation of CrazyJoystick, evaluates its force and torque performance, and usability of the system in three VR applications. Our evaluation of torque rendering found that users can perceive the direction with an accuracy of 92.2%. User studies further indicated that the system significantly improves presence in VR environments. Participants found on-demand haptic feedback intuitive and enjoyable, emphasizing the potential of CrazyJoystick to redefine immersive interactions in XR through portable and adaptive feedback mechanisms. 

A Flying Light Speck, FLS, is a small drone configured with light sources to illuminate different colors and textures. A swarm of FLSs illuminates complex 3D multimedia shapes in a fixed volume, a 3D display. An FLS is a mechanical device. Its failure is the norm rather than an exception, causing a point of an illumination to go dark. In this paper, we use reliability groups with dark standby FLSs to minimize the duration of time a point remains dark. We introduce three techniques to prevent a dark standby FLS from obstructing the user’s field of view, FoV. All three move the FLS out of the user’s FoV. One technique, Suspend:Closest, maximizes the utility of a standby FLS while preventing it from obstructing the user’s FoV. 

One may construct a 3D multimedia display using miniature drones configured with light sources, Flying Light Specks (FLSs). Swarms of FLSs localize to illuminate complex 3D shapes and animated sequences. This requires FLSs to measure their relative pose (distance and angle) accurately. A challenge is how to do this when the sensors used by FLSs have a blind range that prevents them from quantifying their relative pose. Our technique, Swazure, requires FLSs to cooperate to compensate for their sensor's blind range. It implements {\em physical data independence} by abstracting the physical characteristics of the sensors, making point cloud data independent of the sensor hardware. The size of an FLS relative to the minimum distance between points of a point cloud is an important parameter. It may result in potential obstructions that prevent Swazure from quantifying relative pose. We present two techniques, move obstructing and move source, to address this limitation. Our experimental results show the superiority of the Move Obstructing technique. 

This paper presents the design and implementation of a circular flight pattern for use by a 3D multimedia display, a Dronevision (DV). A DV uses drones configured with light sources, Flying Light Specks (FLSs), that are battery powered. The flight pattern enables a swarm of FLSs to enter an opening, granting them access to the charging coils to charge their batteries. We present two algorithms for an FLS to travel from its current coordinate to rendezvous with its assigned slot on the flight pattern, Shortest Distance (SD) and Fastest Rendezvous Time (FRT). In addition to quantifying the tradeoff associated with these algorithms, we present an implementation using a swarm of Crazyflie drones with Vicon localization. 

Swarical, a Swarm-based hierarchical localization technique, enables miniature drones, Flying Light Specks (FLSs), to accurately and efficiently localize and illuminate complex 2D and 3D shapes. Its accuracy depends on the physical hardware (sensors) of FLSs used to track neighboring FLSs to localize themselves. It uses the specification of the sensors to convert mesh files into point clouds that enable a swarm of FLSs to localize at the highest accuracy afforded by their sensors. Swarical considers a heterogeneous mix of FLSs with different orientations for their tracking sensors, ensuring a line of sight between a localizing FLS and its anchor FLS. We present an implementation using Raspberry cameras and ArUco markers. A comparison of Swarical with a state of the art decentralized localization technique shows that it is as accurate and more than 2x faster.