Frontiers in Robotics and AI最新文献

{"title":"A survey of machine learning for estimating workload: considering unknown tasks.","authors":"Joshua Bhagat Smith, Julie A Adams","doi":"10.3389/frobt.2026.1872363","DOIUrl":"10.3389/frobt.2026.1872363","url":null,"abstract":"<p><p>Successful human-robot teaming will require robots to adapt autonomously to a human teammate's internal state, where a critical element is the ability to estimate the human's workload in unknown situations. Existing workload models use machine learning to model the relationship between physiological signals and workload. These methods often struggle to generalize to unknown tasks, as the relative importance of various physiological signals change significantly between tasks. Many of these changes constitute a meaningful shift in the data's distribution, which violates a core assumption made by the underlying machine learning. A survey of machine learning techniques designed to overcome these challenges is presented, where common techniques are evaluated using three criteria: portability, model complexity, and adaptability. These criteria are used to analyze each technique's applicability to estimating workload during unknown tasks in dynamic environments and guide future empirical experimentation.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1872363"},"PeriodicalIF":3.7,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13542377/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148898079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Embodied neuromorphic AI for robotic perception.","authors":"Jorge Dias, Fakhreddine Zayer, Mario Molinara","doi":"10.3389/frobt.2026.1956418","DOIUrl":"https://doi.org/10.3389/frobt.2026.1956418","url":null,"abstract":"","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1956418"},"PeriodicalIF":3.7,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13535528/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148882199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Moonshot goals of soft robotics through embodied intelligence.","authors":"Nana Obayashi","doi":"10.3389/frobt.2026.1929066","DOIUrl":"https://doi.org/10.3389/frobt.2026.1929066","url":null,"abstract":"","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1929066"},"PeriodicalIF":3.7,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13533762/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148882261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ConceptACT: episode-level concepts for sample-efficient robotic imitation learning.","authors":"Jakob Karalus, Friedhelm Schwenker","doi":"10.3389/frobt.2026.1865290","DOIUrl":"10.3389/frobt.2026.1865290","url":null,"abstract":"<p><p>Imitation learning enables robots to acquire complex manipulation skills from human demonstrations, but current methods rely solely on low-level sensorimotor data while ignoring the rich semantic knowledge humans naturally possess about tasks. We present ConceptACT, an extension of Action Chunking with Transformers that leverages episode-level semantic concept annotations during training to improve learning efficiency. Unlike language-conditioned approaches that require semantic input at deployment, ConceptACT uses human-provided concepts (object properties, spatial relationships, task constraints) exclusively during demonstration collection, adding minimal annotation burden. We integrate concepts using a modified transformer architecture in which the final encoder layer implements concept-aware cross-attention, supervised to align with human annotations. Through experiments on two robotic manipulation tasks with logical constraints, we demonstrate that ConceptACT converges faster and achieves superior sample efficiency compared to standard ACT. Crucially, we show that architectural integration through attention mechanisms significantly outperforms naive auxiliary prediction losses or language-conditioned models. These results indicate that properly integrated semantic supervision provides useful inductive biases for manipulation tasks.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1865290"},"PeriodicalIF":3.7,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13506310/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148833502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of a robotic insole-type active assist device on horizontal ground reaction force and center-of-pressure stability during stepping in patients with medial knee osteoarthritis.","authors":"Taku Itami, Takaaki Aoki, Haruhiko Akiyama","doi":"10.3389/frobt.2026.1898805","DOIUrl":"10.3389/frobt.2026.1898805","url":null,"abstract":"<p><p>An insole-type active assist device has been developed as a robotic system to dynamically correct ankle alignment at heel contact in patients with medial knee osteoarthritis. Although our previous feasibility study demonstrated that the device could be safely used during an on-the-spot stepping task, its effects on loading behavior remain unclear. This study aimed to investigate whether dynamic ankle alignment correction using the device alters horizontal ground reaction force variability and center-of-pressure sway during stepping. Force-plate data obtained from six ambulatory patients with medial knee osteoarthritis were analyzed as a secondary biomechanical analysis. Each participant performed repeated stepping trials under two conditions: a non-control condition, in which the device was worn without motor control, and a control condition, in which heel-eversion assistance was provided. Stance phases were extracted using vertical ground reaction force, and horizontal ground reaction force components, center-of-pressure sway measures, peak vertical ground reaction force, and vertical impulse were calculated. Compared with the non-control condition, the control condition reduced the ranges of anterior-posterior and medial-lateral ground reaction force components in all participants. Center-of-pressure rectangular sway area also decreased consistently, and trajectory length tended to decrease, whereas peak vertical ground reaction force and vertical impulse showed little change. These findings suggest that dynamic ankle alignment correction using a robotic insole-type device may reduce horizontal loading variability and center-of-pressure sway during stepping without substantially altering vertical loading. Because this study was based on a small sample and an exploratory secondary analysis, the findings should be interpreted as preliminary biomechanical evidence rather than evidence of clinical effectiveness.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1898805"},"PeriodicalIF":3.7,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13506424/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148833489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A compact external-rail linear actuation mechanism with a high stroke-to-length ratio for wearable exoskeleton applications.","authors":"Tianmai Sun, Filip Stefanovic","doi":"10.3389/frobt.2026.1843206","DOIUrl":"10.3389/frobt.2026.1843206","url":null,"abstract":"<p><strong>Introduction: </strong>Tendon-driven exoskeletons are often limited by mechanical bulk, complex cable routing, and large externally mounted actuators. Similarly, conventional linear actuators used in wearable exoskeleton systems are often limited by low stroke-to-body-length ratios that restrict the range of motion. This study presents the mechanical design of a novel Rail-guided Inline DirEct dRive (RIDER) with a high stroke-to-length ratio for wearable exoskeletons.</p><p><strong>Methods: </strong>The proposed system creates a linearized RIDER system using a \"motor-driven cart\" layout that travels along a toothed twin-rail structure. The prototype system was developed using 3D-printed materials and open-source electronics, and the resultant force-velocity performance was experimentally evaluated under vertical loading. Vertical displacement was measured using an ultrasonic sensor (HC SR-04), and the corresponding velocity was computed via a finite-difference approximation.</p><p><strong>Results: </strong>The actuator demonstrated a maximum free-load velocity of 7.27 cm/s and a maximum force output of 103.7 N prior to slipping. When integrated into a tendon-driven system, the duo configuration produced a 6.22 Nm torque output with a range of motion of 120° or a 10.37 Nm torque output with a range of motion of 72°. The actuator also demonstrates a 190% (i.e., 0.58 vs 0.2) higher stroke-to-length ratio than a representative telescopic actuator of similar geometry.</p><p><strong>Conclusion: </strong>In this study, we show that the RIDER system demonstrates a wearable, rail-based actuation strategy capable of adjustable torque amplification and improved spatial-efficiency integration for human-robot interaction in wearable robotics. The current study focuses on the benchtop mechanical validation of the RIDER system as a proof-of-concept for future integration into wearable exoskeletons. This research is part of a larger study to develop adaptive exoskeletons that enable scalable performance improvements for assistive robotics in the workplace and neurorehabilitation.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1843206"},"PeriodicalIF":3.7,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13506294/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148833449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Advances in smart and adaptive prosthetic and wearable technologies.","authors":"Charikleia Angelidou, Lucas Ferrari Gerez, Kinsey Herrin, Cara Gonzalez Welker","doi":"10.3389/frobt.2026.1934269","DOIUrl":"10.3389/frobt.2026.1934269","url":null,"abstract":"","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1934269"},"PeriodicalIF":3.7,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13503186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148819993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gender and diagnostic differences in children's preferences for social robot design. A mixed-methods study with autistic and neurotypical children.","authors":"Gema Benedicto Rodríguez, Vanessa Zorrilla-Muñoz, Carlos G Juan, Jose Manuel Ferrandez","doi":"10.3389/frobt.2026.1812453","DOIUrl":"10.3389/frobt.2026.1812453","url":null,"abstract":"<p><strong>Introduction: </strong>Autistic children are increasingly engaging with social robots in educational and support contexts, but limited research has compared the perceptual and design preferences of autistic and neurotypical children.</p><p><strong>Methods: </strong>This mixed-methods study examined the robot design preferences of 43 children aged 3-15 years, including 21 autistic and 22 neurotypical children, and included semi-structured interviews with 11 adult stakeholders, comprising six experts and five non-experts. Quantitative analyses explored relationships between robot preference and perceptual features, including size, color, movement, voice, and anthropomorphism, while qualitative thematic and co-occurrence analyses examined perceived benefits, ethical issues, accessibility challenges, and ideal design characteristics.</p><p><strong>Results: </strong>Perceptual characteristics, particularly movement intensity and color multiplicity, influenced robot preference. Across groups, children generally preferred humanoid robots with soft voices and eye movement. Gender-related differences appeared more consistent than diagnostic differences in preferences for size and movement speed. Autistic children highlighted playful and social interaction functions and showed greater variability in preferred personality-related traits. Qualitative findings indicated strong interest in robot-supported interactions, while also raising concerns about accessibility and possible emotional dependency.</p><p><strong>Discussion: </strong>These findings suggest that inclusive social robot design should prioritize modificable sensory features, moderated anthropomorphism, predictable interaction patterns, and personalization mechanisms that account for individual, gender-related, and diagnostic differences.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1812453"},"PeriodicalIF":3.7,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13494466/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148799516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PFEA: a VLM-based high-level natural language planning and feedback embodied agent for human-centered AI.","authors":"Wenbin Ding, Jun Chen, Mingjia Chen, Fei Xie, Jun Wang, Simon X Yang, Philip Dames","doi":"10.3389/frobt.2026.1905578","DOIUrl":"https://doi.org/10.3389/frobt.2026.1905578","url":null,"abstract":"<p><p>The rapid advancement of Large Language Models (LLMs) has led to significant progress in Artificial Intelligence (AI), ushering in a new era of human-centered AI (HAI). Intelligent agents powered by LLMs provide new opportunities for realizing HAI. However, existing LLM-based embodied agents often lack online planning capabilities and may generate actions involving objects that are not present in the current environment. In this paper, we propose a closed-loop framework for planning and evaluation of a vision-language model-based robotic manipulation agent operating in tabletop object rearrangement and manipulation tasks. These tasks require a robot to interpret high-level natural language commands and perform multi-step actions such as stacking objects, sorting objects by category or attribute, placing objects into target containers, and organizing mixed desktop scenes. The proposed architecture consists of a human-robot speech interaction module, a vision-language agent module (including a planner, translator, and evaluator), and an action execution module. Within this framework, the vision-language planner decomposes high-level instructions into executable task steps via Chain-of-Objects Reasoning, enabling a deeper understanding of the visual environment, including spatial relationships and object attributes. Meanwhile, the task evaluator monitors execution outcomes and provides result-oriented feedback, allowing the system to replan when errors occur. Experimental results show that, compared with baseline methods, the proposed agent improves the average task success rate by approximately 20% in both simulation and real-world environments, significantly enhancing its ability to execute complex natural language instructions. This work demonstrates the potential of closed-loop vision-language planning for human-centered robotic manipulation. Code: https://github.com/subforpaper/PFEA.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1905578"},"PeriodicalIF":3.7,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13489843/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148799496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reduced-order state-space reformulation for task-space predictive control of an under-actuated hydraulic boom.","authors":"Elham Kowsari, Reza Ghabcheloo","doi":"10.3389/frobt.2026.1853243","DOIUrl":"10.3389/frobt.2026.1853243","url":null,"abstract":"<p><p>Hydraulic booms used in material handling are typically commanded in cylindrical task-space coordinates, while dynamic models used for control are commonly formulated in joint coordinates. This mismatch leads to unnecessarily high-dimensional system representations when predictive control is applied to underactuated suspended loads. This paper addresses this modeling inconsistency by introducing a reduced-order state-space reformulation of grapple sway dynamics directly in cylindrical task-space velocity coordinates. The proposed input-consistent state transformation eliminates the dependence of the dynamics on input accelerations by embedding actuator-sway coupling within modified velocity states, yielding a nonlinear model driven solely by cylindrical velocity commands. Based on this representation, a nonlinear model predictive control (NMPC) framework is developed for simultaneous goal reaching, sway suppression, and obstacle avoidance. The NMPC cost function is designed to capture the practical trade-off between rapid boom motion and suppression of suspended load oscillations. In addition, approximate hydraulic actuator dynamics identified from a high-fidelity AMESim simulator model of a forwarder crane are incorporated to better reflect realistic boom behavior. Simulation studies in representative boom operation scenarios demonstrate that the proposed formulation enables effective sway regulation and accurate task-space motion control using a reduced set of states without requiring full joint-space models or payload sensing. The results indicate that the proposed cylindrical state-space reformulation simplifies predictive control design for underactuated hydraulic booms while preserving the essential dynamics of the suspended load.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1853243"},"PeriodicalIF":3.7,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13527712/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}