[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83405-en":3,"doc-seo-83405-105":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},83405,13056703020460,"Valentina","https://ap-avatar.wpscdn.com/avatar/be000253dac470eee5d?_k=1778207105932848923",8,"Research & Report","A New Human-Likeness and Comfort Index for Robot Movements Along Prescribed Paths","Human-robot interaction drives growing interest in robot acceptance, which depends on comfort and ergonomics reflected by how humans perceive robot movement quality. This paper links comfort to the human-likeness of robot motion along prescribed end-effector paths by using a kinematic characterization of human movements and their time laws. A human-likeness index is defined via the lognormality principle to characterize trajectories a priori and benchmark trajectory-generation algorithms before execution. Experimental validation with 68 subjects across three robot interaction campaigns shows a globally consistent relationship between comfort preferences and the index distribution.","A New Human-Likeness and Comfort Index for Robot Movements Along Prescribed Paths  \nRosanna Coccaro, Enrico Ferrentino, Antonio Parziale, Angelo Marcelli and Pasquale Chiacchio  \narXiv :2607 .08620v 1 [ cs .RO] 9 Jul 2026  \nAbstract—As human-robot interaction rapidly spreads in numerous fields, the subject of robot acceptance gains increasing importance. Visual similarity to the human body, as occurs for humanoids, is generally not enough to ensure acceptance in physical interaction, as acceptance directly links to comfort and ergonomics, which are measured in terms of the quality of the robot movement perceived by the human. This paper discusses the connection between comfort and similarity of the robot movement to the human one. By considering the kinematic characterization of human movement, this paper focuses on the time laws of such movements, wherein the end-effector path is prescribed. Based on the lognormality principle for modeling human movements, a human-likeness index is defined and used to provide an a priori characterization of trajectories. Such an index can be used to evaluate the performance of trajectory generation algorithms in producing human-like movements before they are actually executed. For validation purposes, 68 subjects are required to judge their comfort. The results of three experimental campaigns involving a physical interaction with a robot demonstrate a globally consistent trend between the preference in terms of perceived comfort and the distribution of the suggested human-likeness index.  \nIndex Terms—Comfort index, human-robot collaboration, human-robot interaction, robot acceptance.  \nI. INTRODUCTION  \nSINCE the emergence of Human-Robot Interaction (HRI)  \nas a field, several studies have concerned the “social”dimension of robots in industry, particularly, in relation to cognitive and perceptual workload for robot operators [1], that can undermine acceptance. A strategy to tackle user robot acceptance goes through the design of robots resembling humans in both their physical aspect and their behavior, as described in [2] . To this extent, recent research has led to the development of brain-inspired intelligent robots that are capable of emulating humans and animals in both their external structures and internal mechanisms. This is achieved through the integration of visual cognition, decision-making, motion control, and musculoskeletal systems [3], [4], [5] . A fundamental premise is that humans tend to favor engaging with machines (and robots) [6] in a manner that resembles their interactions with other humans [7], [8] . This is sustained  \nThis research was conducted in the frame of the Department of Excellence 2023/2027 Project and partially funded by Istituto Nazionale della Previdenza Sociale (INPS) .  \nThe authors are with the Department of Computer Engineering, Electrical Engineering and Applied Mathematics (DIEM), University of Salerno, 84084 Fisciano, Italy (e-mail: [rcoccaro@unisa.it](rcoccaro@unisa.it); [eferrentino@unisa.it](eferrentino@unisa.it); [anparziale@unisa.it](anparziale@unisa.it);  \n[amarcelli@unisa.it](amarcelli@unisa.it); [pchiacchio@unisa.it](pchiacchio@unisa.it))  \nThis article has supplementary material provided by the authors available at [https://dx.doi.org/10.21227/amq5-qp90. The](https://dx.doi.org/10.21227/amq5-qp90. The) source code is also available at [https://github.com/unisa-acg/trajectory](https://github.com/unisa-acg/trajectory) planning matlab/tree/v01r00.  \nby the concept of motor contagion, which posits that an individual’s motor actions are involuntarily influenced by observing and experiencing others’ movements. The degree of motor contagion is influenced by the human likeness of a robot: the greater the resemblance between robot and human movements and appearance, the stronger the motor contagion effect. Movement kinematics, such as the velocity profile and the trajectory of the limb, might also vary the degree of motor resonance evoked in the ob","cbCairdtLJRJLB6y","https://ap.wps.com/l/cbCairdtLJRJLB6y","pdf",3012691,2,1,14,"English","en",105,"# Introduction\n## Human acceptance and comfort\n## Human-like motion and motor contagion\n## Study hypothesis and scope","[{\"question\":\"What problem does the paper address in human-robot interaction?\",\"answer\":\"The paper addresses how to improve robot acceptance by relating perceived comfort and ergonomics to measurable qualities of robot motion.\"},{\"question\":\"How is the proposed human-likeness index constructed?\",\"answer\":\"It models human movement time laws using the lognormality principle and defines an index that characterizes robot trajectories a priori.\"},{\"question\":\"How was the approach validated?\",\"answer\":\"Validation required 68 subjects to judge comfort, and results from three experimental campaigns with physical robot interaction showed a consistent trend between comfort preferences and the human-likeness index 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problem does the paper address in human-robot interaction?","Question",{"text":75,"@type":76},"The paper addresses how to improve robot acceptance by relating perceived comfort and ergonomics to measurable qualities of robot motion.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is the proposed human-likeness index constructed?",{"text":80,"@type":76},"It models human movement time laws using the lognormality principle and defines an index that characterizes robot trajectories a priori.",{"name":82,"@type":73,"acceptedAnswer":83},"How was the approach validated?",{"text":84,"@type":76},"Validation required 68 subjects to judge comfort, and results from three experimental campaigns with physical robot interaction showed a consistent trend between comfort preferences and the human-likeness index 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