[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-86582-en":3,"doc-seo-86582-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},86582,13056703020460,"Valentina","https://ap-avatar.wpscdn.com/avatar/be000253dac470eee5d?_k=1778207105932848923",8,"Research & Report","Automated Synthesis of Facial Mechanisms for Conversational Animatronic Robots","Automated Synthesis of Facial Mechanisms for Conversational Animatronic Robots addresses the scalability bottleneck of socially interactive animatronic faces, where each new geometry demands extensive manual mechanical redesign. The work proposes a parametric, linkage-driven mechanical face template with explicit topology and actuator layout parameterization, enabling systematic scaling and retargeting. A hierarchical design algorithm maps a single 2D portrait to a collision-free, manufacturable internal mechanism using anatomy-guided feasible motion volumes and AU-derived expressiveness objectives. For large-scale deployment, it further introduces dual-identity conversational motion synthesis to model speaking and listening behaviors from audio and produce temporally coherent 3D facial motion, validated via diverse experiments and perceptual studies.","Automated Synthesis of Facial Mechanisms for Conversational Animatronic Robots  \narXiv :2607 . 11688v1 [ cs .RO] 13 Jul 2026  \nZongzheng Zhang∗1 ,2 , Zi Lin∗1, Jiawen Yang 1 , Ziqiao Peng 1 ,  \nJunyan Lao 1 , Lin Cheng4 , Huazhe Xu3 , Hang Zhao3 , Hao Zhao†1 ,2  \n1 Institute for AI Industry Research (AIR), Tsinghua University 2 Beijing Academy of Artificial Intelligence (BAAI)  \n3 Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University 4 Beihang University  \n∗ Equal contribution †Corresponding author  \n[https://zzongzheng0918.github.io/automated-facial-mechanisms-synthesis/](https://zzongzheng0918.github.io/automated-facial-mechanisms-synthesis/)  \n(a)  \n(b)  \n(c)  \nI can’t believe it.  \nBut I reckon that’s    \n(d)  \n(e)  \nFig. 1: We demonstrate our end-to-end physical conversational face system across diverse multi-round interactions: (a) reenactments of Star Wars (Yoda–Luke Skywalker) and (b) Titanic (Rose–Jack); (c) a dialogue between a real elf and a virtual elf; (d) a three-character encounter from the Chinese folktale Legend of the White Snake; and (e) human–robot dialogue.  \nAbstract—Animatronic faces are a central component of socially interactive robots, enabling rich nonverbal communication through facial articulation. However, state-of-the-art animatronic faces are typically tailored systems: each new facial geometry requires extensive manual mechanical redesign, making large-scale personalization prohibitively slow and costly. In this work, we pursue automated and scalable mechanical face synthesis, aiming to rapidly generate a physically realizable facial mechanism fora wide range of facial geometries. We introduce a parametric, linkage-driven mechanical face template whose topology and actuator layout are explicitly parameterized to support systematic scaling and retargeting across diverse facial morphologies. Building on this template, we propose a hierarchical automatic design algorithm that takes a single 2D portrait as input, reconstructs a target 3D face, and synthesizes a collision-free, manufacturable internal mechanism. The algorithm combines anatomy-guided feasible motion volumes, Action Unit (AU)-derived trajectorybased expressiveness objectives, and a collision-driven outerloop refinement strategy. Beyond hardware synthesis, we argue that future mechanical faces deployed at scale must engage in bidirectional, multi-turn conversation, rather than functioning solely as speaking or listening heads. To this end, we develop a dual-identity conversational facial motion synthesis framework  \nthat jointly models speaking and listening behaviors from audio, producing temporally coherent 3D facial motion suitable for physical execution. We validate our system through extensive experiments, including (i) quantitative evaluation of automatic mechanism synthesis across diverse facial geometries, (ii) comparisons against manual mechanical design,(iii) benchmarks on conversational facial motion synthesis and real-time deployment, and (iv) perceptual user studies.  \nI. INTRODUCTION  \nImagine a future where thousands of robots coexist with humans, each endowed with a distinct face, identity, and personality. Rather than sharing a single canonical appearance, these robots would exhibit thousands of unique mechanical faces (from realistic human likenesses to stylized fictional characters) capable of engaging in rich, multi-turn conversations. As illustrated in Fig. 1, such animatronic faces would not merely speak, but participate in bidirectional dialogue, react as listeners, and sustain expressive interactions across diverse narratives and social contexts. Realizing this vision of  \nmassively personalized, conversational mechanical faces represents a foundational step toward socially integrated robotics.  \nHowever, despite decades of progress in animatronic face design [51, 52, 10], today’s state-of-the-art systems remain fundamentally tailored [41, 117, 111] . High-fidelity platforms achieve im","cbCaii9fyULZNJFf","https://ap.wps.com/l/cbCaii9fyULZNJFf","pdf",11377694,4,1,31,"English","en",105,"# Introduction\n## Motivation for scalable conversational animatronic faces\n## Automated, parameterized mechanical face synthesis pipeline","[{\"question\":\"Why do current animatronic face systems not scale to large personalization?\\n\",\"answer\":\"State-of-the-art animatronic faces are typically tailored to a fixed geometry, so adapting to a new facial morphology requires extensive manual mechanical redesign, iterative prototyping, and expert intervention. This makes generating hundreds or thousands of distinct mechanical faces impractically slow and costly.\"},{\"question\":\"What is the core idea behind the automated mechanical face synthesis method?\\n\",\"answer\":\"The approach starts from a parametric mechanical face template whose topology, actuator layout, and kinematic structure are explicitly parameterized. Instead of redesigning mechanisms from scratch, a hierarchical optimization pipeline adapts this template to a target facial geometry to produce collision-free, manufacturable designs with minimal human effort.\"},{\"question\":\"How does the system support conversational behavior beyond speaking-only motion?\\n\",\"answer\":\"It proposes a dual-identity conversational facial motion synthesis framework that jointly models speaking and listening from audio, generating temporally coherent 3D facial motion suitable for physical execution. The goal is bidirectional multi-turn interaction rather than a single role head.\"}]",1784212766,78,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"automated-synthesis-of-facial-mechanisms-for-conversational-animatronic-robots","",{"@graph":36,"@context":85},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":20},"https://docshare.wps.com/document/automated-synthesis-of-facial-mechanisms-for-conversational-animatronic-robots/86582/",{"url":52,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-25","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why do current animatronic face systems not scale to large personalization?","Question",{"text":75,"@type":76},"State-of-the-art animatronic faces are typically tailored to a fixed geometry, so adapting to a new facial morphology requires extensive manual mechanical redesign, iterative prototyping, and expert intervention. This makes generating hundreds or thousands of distinct mechanical faces impractically slow and costly.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is the core idea behind the automated mechanical face synthesis method?",{"text":80,"@type":76},"The approach starts from a parametric mechanical face template whose topology, actuator layout, and kinematic structure are explicitly parameterized. Instead of redesigning mechanisms from scratch, a hierarchical optimization pipeline adapts this template to a target facial geometry to produce collision-free, manufacturable designs with minimal human effort.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the system support conversational behavior beyond speaking-only motion?",{"text":84,"@type":76},"It proposes a dual-identity conversational facial motion synthesis framework that jointly models speaking and listening from audio, generating temporally coherent 3D facial motion suitable for physical execution. The goal is bidirectional multi-turn interaction rather than a single role head.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":21,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":20,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]