[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-86103-en":3,"doc-seo-86103-105":29,"detail-sidebar-cat-0-en-105":82},{"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":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},86103,1374391974468,"Eden","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",6,"Technology","Dual-Arm Robot-Assisted Dressing with Differentiable Clothing Simulation","Assistive robots for dressing can improve daily life for people with physical impairments, yet most methods only achieve partial dressing because garment–limb contact interactions and constraints make remaining garments difficult to handle. A real-time robotic dressing control algorithm is proposed that integrates differentiable clothing simulation. The simulation uses an explicit iterative scheme with intentional high-order bias for efficiency and stability under large time steps. A constrained local model enables high-frequency local compensation of a global differentiable controller. Simulation comparisons and physical experiments across varied user poses validate feasibility and effectiveness for dual-arm, multi-stage dressing.","Dual-Arm Robot-Assisted Dressing with Differentiable Clothing Simulation  \nYiming Liu, Lijun Han, and Hesheng Wang, Senior Member, IEEE  \narXiv :2607 . 10999v1 [ cs .RO] 13 Jul 2026  \nAbstract—The development of assistive robots for dressing tasks serves to augment human convenience and improve the quality of life for individuals with physical impairments. However, due to the intricate contact interactions between garments and the human limbs during dressing, most robot-assisted dressing algorithms can only achieve partial dressing, struggling to handle with the remaining garments under contact constraints. To overcome this challenge, we propose a novel robotic dressing control algorithm that integrates real-time differentiable clothing simulation. The simulation algorithm employs explicit iterative scheme with intentionally introduced high-order bias to enhance computational efficiency while maintaining stability under large time-step conditions. Through simulation, we resolve the garment state under contact constraints, which then enables a multi-stage control strategy for successful dressing assistance. To further improve real-time performance, a constrained local model is introduced along with its corresponding optimization solver, permitting high-frequency local compensation for the differentiable simulation based global controller. By comparing with the Projective Dynamics algorithm in simulation, we validated the realtime computational advantages of our differentiable simulation. Physical dressing experiments were conducted on users with various poses and motion patterns, conclusively demonstrating the feasibility and efficacy.  \nIndex Terms—Robot-assisted dressing, differentiable clothing simulation, human-robot interaction  \nI. INTRODUCTION  \nWith the development of artificial intelligence, assistive robots [1], [2] are increasingly used in daily life, which especially enhances the quality of life for elderly and mobilityimpaired individuals. Among different daily tasks, robotassisted dressing is one of the most common yet critical tasks. As the dressing process necessitates the manipulation of deformable garments while maintaining indirect physical interaction with humans, this task encompasses challenges in both deformable object manipulation and human-robot collaboration, rendering it a representative and demanding benchmark for cooperative robotics. Advancements in this domain hold substantial implications for improving assistive robotic capabilities.  \nDuring dressing process, complex contact interactions arise between garments and the human limbs, especially when partial structures of the clothing have been worn completely.  \n*This work was supported in part by the Natural Science Foundation of China under Grant 62225309, 62073222, U21A20480 and 62361166632, in part by the Open Research Projects of Zhejiang Lab under Grant 2022NB0AB01 .  \nY. Liu, L. Han, and H. Wang are with the Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China (e-mail: [lym5634@sjtu.edu.cn](lym5634@sjtu.edu.cn); lijun [han@sjtu.edu.cn](han@sjtu.edu.cn); [wanghesheng@sjtu.edu.cn](wanghesheng@sjtu.edu.cn)).  \nFor garments like coats, the donned sleeve establishes tight physical contact [3], providing support and constraining the overall motion and deformation of the garment. Approaches [4]–[6] have overlooked these constraints by simplifying garments as independent armholes, thereby failing to address the secondary sleeve dressing problem. To properly account fordeformable garment constraints, it is essential to formulate an appropriate garment model, leveraging clothing simulation to predict contact deformation in constrained dressing tasks.  \nThe effectiveness of assisted dressing is influenced by the user’s pose and motion patterns. Previous work [7]–[9] treats assisted dressing as a synchronized dual-arm trajectory tracking problem. However, when the user’s arms are naturally extended beyond the garment’s shoulde","cbCaijNUXjWsgs5O","https://ap.wps.com/l/cbCaijNUXjWsgs5O","pdf",10355671,1,17,"English","en",105,"# Introduction\n## Challenges in garment–limb contact constraints\n## Need for dual-arm coordinated control\n## Proposed differentiable simulation and multi-stage control contributions","[{\"question\":\"How does the system adapt to different user poses and arm behaviors?\",\"answer\":\"It incorporates predicted human motion trajectories and uses a multi-stage, goal-guided dual-arm control strategy. Additionally, a constrained local model provides high-frequency local compensation to improve performance under varying conditions.\"}]",1784208532,43,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":77,"head_meta":79,"extra_data":81,"updated_unix":27},"dual-arm-robot-assisted-dressing-with-differentiable-clothing-simulation","",{"@graph":35,"@context":76},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/technology/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/dual-arm-robot-assisted-dressing-with-differentiable-clothing-simulation/86103/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-16",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70],{"name":71,"@type":72,"acceptedAnswer":73},"How does the system adapt to different user poses and arm behaviors?","Question",{"text":74,"@type":75},"It incorporates predicted human motion trajectories and uses a multi-stage, goal-guided dual-arm control strategy. 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