https://josephkenny.com 2026-09-24T03:04:55+00:00 always 0.5 https://freight.cargo.site/t/original/i/S3119881251285024188361227150804/robotic_territories.png https://freight.cargo.site/t/original/i/M3119975341614843522764548646356/immersiveDesign.png https://freight.cargo.site/t/original/i/E3119997679404431676166725215700/aiApprenticeship.png https://freight.cargo.site/t/original/i/F3120030361334886370715937318356/compas_xr_lead_image.png https://freight.cargo.site/t/original/i/Z3120069023625982785606945121748/masT2Casch.png https://freight.cargo.site/t/original/i/H3120078321744226627053856269780/arTimberAssembly.png https://freight.cargo.site/t/original/i/P3120100473184806147842142414292/caa.png https://freight.cargo.site/t/original/i/P3120134754816906914483670656468/protoPlasto.png https://freight.cargo.site/t/original/i/L3120195554233909448964352550356/impactPrinting.png https://freight.cargo.site/t/original/i/P3120245434432798944402727282132/endlessAssemblies.png https://freight.cargo.site/t/original/i/U3120473951277984764652510815700/buildingStudioRedux.png https://freight.cargo.site/t/original/i/R3120555148071566339027634791892/Intro-Image_AG-Office_B-W.png https://freight.cargo.site/t/original/i/J3120614962948944171482127836628/WEBEXPORTS.png https://freight.cargo.site/t/original/i/I3120655965633801450125077816788/odunpazari.png https://freight.cargo.site/t/original/i/V3120678709454673409948195005908/stickPlay.png https://freight.cargo.site/t/original/i/H3120697002721836426236341560788/LLM.png https://freight.cargo.site/t/original/i/Q3120722396970896896647834936788/flysEye.png https://freight.cargo.site/t/original/i/B3126799205473222681074972796372/marsSanctuary.png https://freight.cargo.site/t/original/i/K3126804824775742646699714717140/rippleEffect.png https://freight.cargo.site/t/original/i/N3128149325531222814582728336852/aModularPerformance.png https://freight.cargo.site/t/original/i/Y3128159408005024670159774197204/aPsuedoImage.png https://freight.cargo.site/t/original/i/W3128162426003035593484675884500/diesteLaborReconstruction.png https://freight.cargo.site/t/original/i/V3128182222661393873027569591764/maskingTimeInThirds.png https://freight.cargo.site/t/original/i/I3128302639040657073132965242324/cover-page-two.png https://freight.cargo.site/t/original/i/Y3128306282327951862990538057172/piedmontRedevelopment.png https://freight.cargo.site/t/original/i/S3128405116772965329942634603988/highlineStudy.png https://freight.cargo.site/t/original/i/Y3128409375904811020593588118996/vaultingSpace.png https://freight.cargo.site/t/original/i/H3128438964242497577756156011988/generationOfSection-2.png https://freight.cargo.site/t/original/i/Q3128472401511781858490378134996/spatialSequence.png https://josephkenny.com/text-index-(desktop) 2026-09-24T03:04:55+00:00 always 0.5 https://josephkenny.com/information 2026-09-24T03:22:22+00:00 always 0.5 https://freight.cargo.site/t/original/i/L3109218752211167592709579384276/kenny_headshot.png https://josephkenny.com/example-project 2026-09-11T21:30:10+00:00 always 0.5 https://freight.cargo.site/t/original/i/X3119769018877556265793244145108/0_IMG_4651.JPG https://freight.cargo.site/t/original/i/R3119798067647978666951427270100/DIS 2026 - RoboticTerritories: Supporting Varying Levels of Automation Through AR for Large-Scale Human–Robot Assembly DIS 2026 Supplementary video : Illustrating the RoboticTerritories system in use. The video demonstrates how users interact with a phone-based AR interface to coordinate large-scale block assembly through three interaction modes, Inference, Mimic, and Realtime Mimic, each offering distinct levels of automation and user-defined control. https://freight.cargo.site/t/original/i/C3119802133181245304020636575188/DIS 2026 - RoboticTerritories: Supporting Varying Levels of Automation Through AR for Large-Scale Human–Robot Assembly (30 Sec.) DIS 2026 Teaser video : Illustrating the RoboticTerritories system in use. The video demonstrates how users interact with a phone-based AR interface to coordinate large-scale block assembly through three interaction modes, Inference, Mimic, and Realtime Mimic, each offering distinct levels of automation and user-defined control. https://freight.cargo.site/t/original/i/B3119808266151800746161552795092/03_inference_diagrams.png Inference mode diagram and photo illustrating the system-suggested stage of the workflow: (A) An interface image depicting the system-suggested assembly goal (shown as semi-transparent orange cubes), next assembly task (shown as a semi-transparent red cube), and robot trajectory displayed in the AR environment. (B) Diagram illustrating an overview of the system-suggestion stage of the workflow, including interface elements, spatial zones, and key system representations as indicated in the legend. https://freight.cargo.site/t/original/i/A3119814001115406053945183348180/03_mimic_interaction_diagram.png Mimic mode diagram and photo illustrating the user trajectory definition and execution stages of the workflow: (A) Diagram illustrating an overview of the trajectory definition stage. The goal appears as solid and semi-transparent (white) cubes around the anchor block (red), both in the robot zone and the mirrored, rescaled human zone. The user defines waypoints and target points using the Set and Undo buttons, which together describe the robot’s trajectory. These points are shown as yellow spheres and cones in the human zone and as corresponding cyan points in the robot zone, with interface elements and application representations indicated in the legend. (B) A photo of the interface depicting the execution stage AR system visualization and robot trajectory, which the user can execute. https://freight.cargo.site/t/original/i/A3119814086763638788178631501268/03_realtime_mimic_interaction.png Realtime Mimic mode diagram and photos illustrating two stages of the workflow: (A) An image of a user utilizing the mode to pick up a block. (B) A diagram illustrating a user selecting an assembly goal and pressing the Follow Me button to begin guiding the robot. The movement traced by the user’s phone in the human zone (yellow) is mirrored and rescaled by the robot in the robot zone (cyan), with interface elements and application representations indicated in the legend. (C) An image of a user utilizing the phone to guide the robot approximately 30 cm above the block prior to placement. https://freight.cargo.site/t/original/i/O3119816095079112837011225486804/2_IMG_4744.JPG https://freight.cargo.site/t/original/i/W3119816260491066945964774827476/inference_01.JPG https://freight.cargo.site/t/original/i/J3119816744090909582334379992532/DSC_0917.jpg https://freight.cargo.site/t/original/i/S3119817585705161201258962920916/0_IMG_4720.JPG https://freight.cargo.site/t/original/i/I3119820239582890853631025259988/00_teaser_updated.png RoboticTerritories is a phone-based AR system that supports the human-robot collaboration assembly of large foam blocks through three distinct interaction modes: Inference, Mimic, and Realtime Mimic. These modes range from the highest level of automation on the left to the most user-defined control on the right. https://freight.cargo.site/t/original/i/L3119822558375514407069082494420/IMG_4623.JPG https://freight.cargo.site/t/original/i/H3119839777599450475692295759316/04_systems_1_opt2.png https://freight.cargo.site/t/original/i/A3119858237182458060545759684052/IMG_4551.jpg https://freight.cargo.site/t/original/i/L3119858910783764656123746493908/DSC_1203.jpg https://freight.cargo.site/t/original/i/T3119859353321154984415889761748/DSC_1131.jpg https://freight.cargo.site/t/original/i/K3119859654925420589567058683348/DSC_1202.jpg https://freight.cargo.site/t/original/i/F3119860088405459577667812107732/DSC_1216.jpg https://freight.cargo.site/t/original/i/H3119861981982185488026995041748/realtime_mimic.JPG https://freight.cargo.site/t/original/i/Y3119862341324760043889060521428/DSC_1150.JPG https://freight.cargo.site/t/original/i/E3119862686537128639289609463252/DSC_1183.JPG https://freight.cargo.site/t/original/i/D3119862763995007004796016698836/DSC_1144.jpg https://freight.cargo.site/t/original/i/Z3119862844183003493211437573588/DSC_1156.JPG https://josephkenny.com/00pixelate 2026-09-11T21:30:10+00:00 always 0.5 https://freight.cargo.site/t/original/i/X3119769018877556265793244145108/0_IMG_4651.JPG https://freight.cargo.site/t/original/i/P3119907155033155974630536160724/00_devices2.png Pixelate application deployed across three device contexts. (A) Running the application on a mobile phone. (B) Running the application in a desktop environment. (C) Running the application through a head-mounted display. https://freight.cargo.site/t/original/i/R3119922023533154498224458343892/00_interface_and_interactions.png Interface and interaction modes of the application. (A) The primary user interface, including the shared pixel canvas, interaction tools, color controls, action history, and interface legend. (B) Randomized interaction, which selects pixels according to a stochastic pattern. (C) Linear incremental selection, which extends selection step-by-step across adjacent pixels. (D) Free-form touch selection, allowing users to directly mark pixels through touch input. (E) Multi-user selection, showing simultaneous local and remote selections within the shared canvas. https://freight.cargo.site/t/original/i/Q3119922211081201495629469623764/02_data_model.png Configuration and runtime event management of the system data model. ScreenData stores persistent session and pixel-grid state, UserCurrentSelection manages tran- sient selection locks, and InteractionLog records append- only interaction events used to synchronize updates across connected clients. https://freight.cargo.site/t/original/i/X3119924479145278846366259914196/05_output_diversity.png Collaborative output diversity across the shared display. (A) Final display state showing the aggregated result of all user contributions. (B), (C), and (F) show outputs composed through contributions from multiple users. (D) and (E) show single-user contributions, illustrating individually produced forms within the broader collaborative canvas https://freight.cargo.site/t/original/i/A3119926753112314300690106721748/03_events_3p25x2.png Per-minute event counts over the 1-hour 18-minute session: 4,413 interaction events (green) and 9,402 selection events (red), showing initial peak activity followed by sustained engagement. https://freight.cargo.site/t/original/i/J3119927135587105924983949927892/meta_quest_close_up.jpg https://freight.cargo.site/t/original/i/Z3119930050541604452567296288212/Copy-of-Copy-of-IMG_3780.jpg https://freight.cargo.site/t/original/i/O3119930144988934109960200562132/IMG_3656.jpg https://freight.cargo.site/t/original/i/F3119930752274195760552349312468/IMG_9802.jpg https://freight.cargo.site/t/original/i/Y3119931393206318601590720210388/IMG_9840.jpg https://freight.cargo.site/t/original/i/M3119931640946091511509998413268/IMG_9833.jpg https://freight.cargo.site/t/original/i/K3119931961015547934444428502484/IMG_9865.jpg https://freight.cargo.site/t/original/i/O3119932208312598986594677466580/IMG_9850.jpg https://freight.cargo.site/t/original/i/R3119932924046269046525280167380/Copy-of-DSC_2099.jpg https://freight.cargo.site/t/original/i/P3119933017368347315421901792724/DSC_2104.jpg https://freight.cargo.site/t/original/i/K3119933664978191511143130375636/DSC_2090.jpg https://freight.cargo.site/t/original/i/N3119933896300362195460907640276/random_specific-06.png https://freight.cargo.site/t/original/i/U3119943708972085228962051565012/pixelate.png https://josephkenny.com/01roboticterritories 2026-09-11T21:30:10+00:00 always 0.5 https://freight.cargo.site/t/original/i/X3119769018877556265793244145108/0_IMG_4651.JPG https://freight.cargo.site/t/original/i/R3119798067647978666951427270100/DIS 2026 - RoboticTerritories: Supporting Varying Levels of Automation Through AR for Large-Scale Human–Robot Assembly DIS 2026 Supplementary video : Illustrating the RoboticTerritories system in use. The video demonstrates how users interact with a phone-based AR interface to coordinate large-scale block assembly through three interaction modes, Inference, Mimic, and Realtime Mimic, each offering distinct levels of automation and user-defined control. https://freight.cargo.site/t/original/i/C3119802133181245304020636575188/DIS 2026 - RoboticTerritories: Supporting Varying Levels of Automation Through AR for Large-Scale Human–Robot Assembly (30 Sec.) DIS 2026 Teaser video : Illustrating the RoboticTerritories system in use. The video demonstrates how users interact with a phone-based AR interface to coordinate large-scale block assembly through three interaction modes, Inference, Mimic, and Realtime Mimic, each offering distinct levels of automation and user-defined control. https://freight.cargo.site/t/original/i/B3119808266151800746161552795092/03_inference_diagrams.png Inference mode diagram and photo illustrating the system-suggested stage of the workflow: (A) An interface image depicting the system-suggested assembly goal (shown as semi-transparent orange cubes), next assembly task (shown as a semi-transparent red cube), and robot trajectory displayed in the AR environment. (B) Diagram illustrating an overview of the system-suggestion stage of the workflow, including interface elements, spatial zones, and key system representations as indicated in the legend. https://freight.cargo.site/t/original/i/A3119814001115406053945183348180/03_mimic_interaction_diagram.png Mimic mode diagram and photo illustrating the user trajectory definition and execution stages of the workflow: (A) Diagram illustrating an overview of the trajectory definition stage. The goal appears as solid and semi-transparent (white) cubes around the anchor block (red), both in the robot zone and the mirrored, rescaled human zone. The user defines waypoints and target points using the Set and Undo buttons, which together describe the robot’s trajectory. These points are shown as yellow spheres and cones in the human zone and as corresponding cyan points in the robot zone, with interface elements and application representations indicated in the legend. (B) A photo of the interface depicting the execution stage AR system visualization and robot trajectory, which the user can execute. https://freight.cargo.site/t/original/i/A3119814086763638788178631501268/03_realtime_mimic_interaction.png Realtime Mimic mode diagram and photos illustrating two stages of the workflow: (A) An image of a user utilizing the mode to pick up a block. (B) A diagram illustrating a user selecting an assembly goal and pressing the Follow Me button to begin guiding the robot. The movement traced by the user’s phone in the human zone (yellow) is mirrored and rescaled by the robot in the robot zone (cyan), with interface elements and application representations indicated in the legend. (C) An image of a user utilizing the phone to guide the robot approximately 30 cm above the block prior to placement. https://freight.cargo.site/t/original/i/O3119816095079112837011225486804/2_IMG_4744.JPG https://freight.cargo.site/t/original/i/W3119816260491066945964774827476/inference_01.JPG https://freight.cargo.site/t/original/i/J3119816744090909582334379992532/DSC_0917.jpg https://freight.cargo.site/t/original/i/S3119817585705161201258962920916/0_IMG_4720.JPG https://freight.cargo.site/t/original/i/I3119820239582890853631025259988/00_teaser_updated.png RoboticTerritories is a phone-based AR system that supports the human-robot collaboration assembly of large foam blocks through three distinct interaction modes: Inference, Mimic, and Realtime Mimic. These modes range from the highest level of automation on the left to the most user-defined control on the right. https://freight.cargo.site/t/original/i/L3119822558375514407069082494420/IMG_4623.JPG https://freight.cargo.site/t/original/i/H3119839777599450475692295759316/04_systems_1_opt2.png https://freight.cargo.site/t/original/i/A3119858237182458060545759684052/IMG_4551.jpg https://freight.cargo.site/t/original/i/L3119858910783764656123746493908/DSC_1203.jpg https://freight.cargo.site/t/original/i/T3119859353321154984415889761748/DSC_1131.jpg https://freight.cargo.site/t/original/i/K3119859654925420589567058683348/DSC_1202.jpg https://freight.cargo.site/t/original/i/F3119860088405459577667812107732/DSC_1216.jpg https://freight.cargo.site/t/original/i/H3119861981982185488026995041748/realtime_mimic.JPG https://freight.cargo.site/t/original/i/Y3119862341324760043889060521428/DSC_1150.JPG https://freight.cargo.site/t/original/i/E3119862686537128639289609463252/DSC_1183.JPG https://freight.cargo.site/t/original/i/D3119862763995007004796016698836/DSC_1144.jpg https://freight.cargo.site/t/original/i/Z3119862844183003493211437573588/DSC_1156.JPG https://josephkenny.com/02immersivedesign 2026-09-11T21:30:10+00:00 always 0.5 https://freight.cargo.site/t/original/i/X3119769018877556265793244145108/0_IMG_4651.JPG https://freight.cargo.site/t/original/i/B3119974812267075583595255473620/immersiveDesign.png https://freight.cargo.site/t/original/i/K3119976448179680272379421435348/downstairs.png Student Work by Ally J. Robertson and Julianne Somar https://freight.cargo.site/t/original/i/R3119977246683890991044782237140/FUNHOUSE.png Student work by Tom Billington and Jonanna I. Tafolla https://freight.cargo.site/t/original/i/M3119978255831472287399512942036/Poster-Image-Upscale_Dark.png Example work by Shravan Arun https://freight.cargo.site/t/original/i/J3119978850923436105269648074196/Screenshot-2025-12-04-080840.png Student work by Lucia Tian https://freight.cargo.site/t/original/i/W3119979822273638794593507517908/DSC_1401.JPG https://freight.cargo.site/t/original/i/Y3119979988681717083527372645844/DSC_1478.JPG https://freight.cargo.site/t/original/i/C3119980142066394056422294332884/DSC_1594.JPG https://freight.cargo.site/t/original/i/U3119980292185997328270625383892/DSC_1515.JPG https://freight.cargo.site/t/original/i/R3119980530665504713187708675540/DSC_1544.JPG https://freight.cargo.site/t/original/i/W3119980752063327085849747170772/DSC_1511.JPG https://freight.cargo.site/t/original/i/O3119982103361117461369241249236/Screenshot-2025-12-04-080730.png Student Work by Lucia Tian https://freight.cargo.site/t/original/i/H3119982983842658843599849432532/PHASE3.png Student work by Tom Billington and Jonanna I. Tafolla https://freight.cargo.site/t/original/i/V3119983504096181954430333658580/DSC_1456.JPG https://josephkenny.com/03aiassistedapprenticeship 2026-09-11T21:30:10+00:00 always 0.5 https://freight.cargo.site/t/original/i/X3119769018877556265793244145108/0_IMG_4651.JPG https://freight.cargo.site/t/original/i/I3119997375771024222907505616340/aiApprenticeship.png https://freight.cargo.site/t/original/i/X3119998781154668222543405032916/Layout.png Spatial layout of the experimental workspace, divided into Tool, PPE, Material, and Task Areas. https://freight.cargo.site/t/original/i/L3119999904174000685907197863380/StudyLineChatUpdated.png Comparison of visual references used during task execution. (A) Ground truth string line setup from the experiment. (B) AI-generated schematic response. (C) Web-retrieved reference images. (D–G) Tool and procedural depictions comparisons from web retrieved vs AI generated during LLM guidance. https://freight.cargo.site/t/original/i/W3120000176281922517196793750996/Responses.png LLM-generated responses to participant photo prompts. Feedback on wall quality and mortar cleanup. (Left) Identification of the brick jointer tool from a user-submitted image (Right) https://freight.cargo.site/t/original/i/S3120000652853555661483059750356/Sequence.png Sequence of steps for Tasks Completion. https://freight.cargo.site/t/original/i/D3120001197881056063305471796692/FinalWalls.png Final wall assemblies showing individual participant contributions by row. https://freight.cargo.site/t/original/i/I3120005060057416031800584086996/update_images_DSC_blinded_0348_background_updates.jpg https://freight.cargo.site/t/original/i/I3120005355758723533364696491476/DSC_0228.JPG https://freight.cargo.site/t/original/i/G3120005529785307124740606436820/gpt_phone_image.jpg https://freight.cargo.site/t/original/i/E3120005779388201186104549352916/DSC_0132.jpg https://freight.cargo.site/t/original/i/T3120006967506093485589349836244/file-Xt3jKgu92kqZceB8Ubi3qo-bab088e3-e4b7-4379-bdfb-f8884b8b74278050185260922369121.jpg https://freight.cargo.site/t/original/i/S3120007825777755003073657873876/DSC_0744.jpg https://freight.cargo.site/t/original/i/S3120008455973872793213069731284/DSC_0373.jpg https://freight.cargo.site/t/original/i/K3120008562227118657780087039444/DSC_0536.jpg https://freight.cargo.site/t/original/i/P3120008659791948063629905536468/DSC_0024.jpg https://josephkenny.com/04compasxr 2026-09-11T21:30:10+00:00 always 0.5 https://freight.cargo.site/t/original/i/X3119769018877556265793244145108/0_IMG_4651.JPG https://freight.cargo.site/t/original/i/F3120029578787109275809338664404/compas_xr_lead_image.png https://freight.cargo.site/t/original/i/B3120032167326471419102169179604/example_1.jpg Example Project : AR Timber Assembly | Enabling Human-Robot Cooperation for Reconfigurable Timber Assembly, Princeton University: Mitterberger, Alexi, Kenny in collaboration with TU, Munich: Dörfler, Atanasova, Saral https://freight.cargo.site/t/original/i/E3120032575313110097336322270676/example_3.jpg Example 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