[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84441-en":3,"doc-seo-84441-105":28,"detail-sidebar-cat-0-en-105":89},{"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":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":13,"seo_description":14,"update_tm":26,"read_time":27},84441,1099513958762,"Logic","https://ap-avatar.wpscdn.com/avatar/1000023916a998db790?x-image-process=image/resize,m_fixed,w_180,h_180&k=1782109480056885918",8,"Research & Report","Towards Online Robot Interaction Adaptation to Human Upper-limb Mobility Impairments in Return-to-Work Scenarios","Work environments often fail to be inclusive for people with upper-body disabilities, limiting their ability to participate actively in work. The paper introduces an online adaptive human-robot interaction framework that supports users with impaired arm mobility by embedding joint-limit mobility modeling into a hierarchical optimal controller. The robot generates reactive, mobility-aware behavior in real time, guiding the impaired limb to use residual functional range. Experiments in handover tasks across different impairments and postures report quantitative and qualitative improvements, enabling personalized interaction within users’ motion limits.","Towards Online Robot Interaction Adaptation to Human Upper-limb Mobility Impairments in Return-to-Work Scenarios  \nMarta Lagomarsino and Francesco Tassi  \narXiv :2510 .05425v2 [ cs .RO] 11 Jul 2026  \nAbstract—Work environments are often inadequate and lack inclusivity for individuals with upper-body disabilities. This paper presents a novel online framework for adaptive human-robot interaction (HRI) that accommodates users’ arm mobility impairments, ultimately aiming to promote active work participation. Unlike traditional physical HRI approaches that assume ablebodied users, our method integrates a mobility model for specific joint limitations into a hierarchical optimal controller. This allows the robot to generate reactive, mobility-aware behaviour online and guides the user’s impaired limb to exploit residual functional mobility. The framework was tested in handover tasks involving different upper-limb mobility impairments (i.e., emulated elbow or shoulder arthritis, and wrist blockage), under both standing and seated configurations with task constraints using a mobile manipulator, and complemented by quantitative and qualitative comparisons with state-of-the-art approaches. Preliminary results indicated that the framework can personalise the interaction to fit within the user’s impaired range of motion and encourage joint usage based on the severity of their functional limitations.  \nI. INTRODUCTION  \nMore than one billion people worldwide live with a disability, with nearly 200 million experiencing significant difficulties in daily functioning. Although laws support disabled employment, only 27% of working-age disabled individuals are employed, compared to 56% of non-disabled individuals [1] . Employed individuals with upper-body limitations are frequently assigned low-value tasks, highlighting persistent labour market barriers. This exclusion reduces independence, social participation, and quality of life, in addition to causing economic losses [2] . Despite the incredible advances in rehabilitation, including AIdriven physical therapy and robotic-assisted strategies, complete functional restoration is often difficult [3] . With an ageing workforce and rising work-related health conditions, addressing disability employment is more urgent than ever.  \nPhysically assistive robots offer a valuable opportunity to promote accessibility and independence in the workplace for individuals with upper-body mobility impairments [4] . Assistive exoskeletons, for example, have shown great potential in compensating for arm muscular weakness and enabling users to  \nThis work was supported by the Italian National Institute for Insurance against Accidents at Work (INAIL) under ergoCub-CORE project and the Italian Ministry of University and Research (MUR) under the Fondo Italianoper la Scienza (FIS 3), project EPIC (FIS-2024-02654) .  \nThe authors are with the Human-Robot Interfaces and Interaction (HRII) Laboratory, Istituto Italiano di Tecnologia, Genoa, Italy.  \nCorresponding author’s email: marta .lagomarsino@iit .it Digital Object Identifier (DOI): see top of this page.  \nperform daily activities [5] . However, they also present limitations, including discomfort from additional weight, operational pressures that may cause irritation in long-term usage, and restrictions on natural movement, mobility, and postural balance. An alternative approach involves teleoperated robotic systems, where a user remotely controls an external robot or manipulator for assistance in pick-and-place tasks [6] . While effective in certain scenarios, this method does not exploit residual user upper-limb mobility and may inadvertently contribute to physical inactivity, further reducing motor function over time.  \nBeyond wearable and teleoperated robotic assistance, adapting the work environment can enhance functional interactions and improve accessibility for impaired users. In this context, collaborative robots (CoBots) constitute a promising solution [4], ","cbCaikDHWGoiLCYb","https://ap.wps.com/l/cbCaikDHWGoiLCYb","pdf",3921037,1,"English","en",105,"# Introduction\n## Inclusive work and disability employment barriers\n## Limitations of existing assistive robotics\n## Collaborative robots and adaptation to impairments\n## Gaps in prior human-robot collaboration research\n## Paper contribution and proposed mobility-aware framework","[{\"question\":\"What problem does the paper address in return-to-work scenarios?\",\"answer\":\"It addresses the lack of inclusive workplace interaction for people with upper-body mobility impairments, where existing robot assistance often assumes able-bodied users.\"},{\"question\":\"How does the proposed framework adapt robot behavior to a user’s impairments?\",\"answer\":\"It integrates a mobility model representing specific joint limitations into a hierarchical optimal controller, enabling reactive, mobility-aware behavior online.\"},{\"question\":\"What kinds of tasks and conditions were used to test the framework?\",\"answer\":\"The framework was evaluated in handover tasks with emulated elbow or shoulder arthritis and wrist blockage, under both standing and seated setups, using a mobile manipulator and task 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