Frontiers in Robotics and AI最新文献

{"title":"High-precision universality? A matched-pair sawbone study on the learning curve, accuracy, and implant interchangeability of a novel open-platform robotic UKA system.","authors":"Pengyu Zhan, Ziyue Liu, Boran Liang, Yugang Xing, Xingyu Liu, Yiling Zhang, Jing Chen","doi":"10.3389/frobt.2026.1886514","DOIUrl":"10.3389/frobt.2026.1886514","url":null,"abstract":"<p><strong>Background: </strong>Robotic-assisted unicompartmental knee arthroplasty (UKA) improves implant positioning over conventional techniques, but commercial systems commonly bind the robotic platform to a single implant manufacturer, restricting clinical flexibility. Open-platform systems offer a vendor-neutral alternative, yet their effect on novice execution precision and workflow stability during implant switching remains insufficiently characterized.</p><p><strong>Methods: </strong>A prospective exploratory matched-pair case series was conducted on standardized synthetic bone models (Sawbones). Two robotic-naïve medical students, after identical training and baseline assessment, each performed 20 consecutive robotic UKA procedures on the ROPA open-platform system (Beijing Changmugu Medical Technology). Operator A used a single implant (Sigma HP Uni, DePuy Synthes); Operator B alternated between two manufacturer-specific workflows (DePuy Synthes; Kangernuo Medical). Because each condition included only one operator, observed differences reflect combined operator- and workflow-related factors that cannot be disentangled. Learning curves were assessed by Cumulative Sum (CUSUM). Three-dimensional resection accuracy was quantified by high-precision laser scanning. Overall perceived workload was assessed with NASA-TLX.</p><p><strong>Results: </strong>The precision CUSUM oscillated around zero for both operators (peak amplitudes +0.30 and -0.54 mm), indicating sub-millimeter accuracy from the first case without a detectable learning phase. All 40 cases fell within the ±1 mm safe zone (P > 0.05 across resection depths). Tibial valgus deviation was greater in Operator B (1.74° ± 1.33° vs. 0.97° ± 0.96°; P = 0.028, Wilcoxon signed-rank test), and the mean deviation of both operators remained below the ±2° degree threshold. Operator B reached the operative-time inflection point earlier (Case 5 vs. 10) and reported lower NASA-TLX workload (32.05 ± 25.60 vs. 38.35 ± 23.72, P = 0.010); this difference cannot be attributed to workflow alone.</p><p><strong>Conclusion: </strong>Under sawbone conditions-which cannot reproduce soft-tissue balancing, bleeding, anatomical variability, patient-specific deformity, or intraoperative decision-making-this two-operator exploratory evaluation found no evidence of compromised accuracy during alternating-implant workflows, with all 40 cases sub-millimeter. Findings are hypothesis-generating pre-clinical observations requiring validation in adequately powered, multi-operator prospective studies before clinical inference.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1886514"},"PeriodicalIF":3.7,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13654760/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149168289","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":"SSS-DDQN solution-space best-first search for robust trajectory tracking of Mecanum robots under partial observability.","authors":"Oorappan G M, Lakshmanan S A","doi":"10.3389/frobt.2026.1896260","DOIUrl":"https://doi.org/10.3389/frobt.2026.1896260","url":null,"abstract":"<p><p>Robust trajectory tracking of Mecanum-wheel mobile robots under partial observability is challenging due to nonlinear motion coupling, noisy measurements, sensor dropout, and external disturbances. In this study, we propose an SSS*-DDQN solution-space best-first search controller for robust trajectory tracking of a four-Mecanum-wheel mobile robot. The proposed framework integrates extended Kalman filter (EKF)-based belief-state estimation, QMDP belief sampling, DDQN value evaluation, and SSS* OPEN-list search with LIVE/SOLVED node refinement. The EKF estimates the hidden robot state under noisy observations and dropout, the DDQN provides learned long-term value evaluation, and the SSS* search refines promising corrective-action clusters using beta-bound pruning, delayed MIN-sibling refinement, bounded OPEN-list management, and secondary lookahead. The controller is evaluated using lemniscate trajectory tracking and compared with EKF-belief PER-DDQN, QMDP-PER-DDQN, Alpha-Beta Minimax, and AB-DDQN Hybrid controllers. The proposed SSS*-DDQN achieved the best overall ranking with <math> <mrow> <msub><mrow><mtext>RMSE</mtext></mrow> <mrow><mi>x</mi> <mi>y</mi></mrow> </msub> <mo>=</mo> <mn>0.01906</mn></mrow> </math> m, <math> <mrow> <msub><mrow><mtext>MAE</mtext></mrow> <mrow><mi>x</mi> <mi>y</mi></mrow> </msub> <mo>=</mo> <mn>0.016074</mn></mrow> </math> m, and a cumulative reward of 1843.6. Compared with the AB-DDQN Hybrid baseline, it reduced <math> <mrow> <msub><mrow><mtext>RMSE</mtext></mrow> <mrow><mi>x</mi> <mi>y</mi></mrow> </msub> </mrow> </math> by 12.93% and <math> <mrow> <msub><mrow><mtext>MAE</mtext></mrow> <mrow><mi>x</mi> <mi>y</mi></mrow> </msub> </mrow> </math> by 17.80%. Statistical validation over multiple stochastic trials further showed the lowest mean <math> <mrow> <msub><mrow><mtext>RMSE</mtext></mrow> <mrow><mi>x</mi> <mi>y</mi></mrow> </msub> </mrow> </math> of <math><mrow><mn>0.01847</mn> <mo>±</mo> <mn>0.00132</mn></mrow> </math> m and <math> <mrow> <msub><mrow><mtext>MAE</mtext></mrow> <mrow><mi>x</mi> <mi>y</mi></mrow> </msub> </mrow> </math> of <math><mrow><mn>0.01554</mn> <mo>±</mo> <mn>0.00128</mn></mrow> </math> m, with narrow 95% confidence intervals. The results confirm that the proposed SSS*-DDQN improves robust action selection and provides consistent tracking performance under partial observability.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1896260"},"PeriodicalIF":3.7,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13655388/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184381","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":"Efficient multi-robot exploration using deterministic and metaheuristic methods.","authors":"Faiza Gul, Imran Mir, Manzar Abbas, Agostino Forestiero","doi":"10.3389/frobt.2026.1781310","DOIUrl":"10.3389/frobt.2026.1781310","url":null,"abstract":"<p><p>Autonomous exploration is a critical challenge in the use of robots across many applications. Nonetheless, current methodologies exhibit inadequate exploration rates, principally attributable to limited global coverage and infrequent decision-making. To mitigate these restrictions, we offer EMREL (Efficient Multi-Robot Exploration), a hybrid optimization method intended to enable rapid multi-robot exploration in intricate, unfamiliar environments. Our methodology implements the deterministic Coordinated Multi-Robot Exploration (CME) formulation, with cost and utility values organized into a Frontier Information Structure (FIS) shared across all robots. The deterministic cost and utility initially direct the prioritization of neighboring cells surrounding each robot. Subsequently, the stochastic optimizer (Crayfish Optimizer) enhances search space by improving overall solutions. This suggests that robots first evaluate their environment using a deterministic method before moving forward under the control of a stochastic algorithm. We evaluated the suggested hybrid technique on both ordinary and complicated maps and compared it with contemporary algorithms. The simulations show that the proposed method outperforms the contemporary algorithms in exploration rate, temporal efficiency, and number of failed simulation runs. These research results demonstrate the potential of EMREL as a versatile, superior, and efficient approach for robotic exploration, establishing a framework for potential developments in multi-robot system design.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1781310"},"PeriodicalIF":3.7,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13655392/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149169930","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":"Tactile regulation with pocket-sized robots: reducing movement and heart rate in children through hand-held interaction.","authors":"Morten Roed Frederiksen, Kasper Støy, Maja Matarić","doi":"10.3389/frobt.2026.1810778","DOIUrl":"10.3389/frobt.2026.1810778","url":null,"abstract":"<p><p>Periods of heightened arousal or restlessness can interfere with children's ability to remain physically calm in everyday settings such as classrooms. Handheld tactile technologies may offer a simple and engaging way to support brief moments of structured sensory-motor engagement. This paper investigates how a pocket-sized tactile device influences physiological and behavioral markers of calmness in typically developing children. Building on prior work examining heart-rate modulation, we present new findings on how a handheld rhythm-matching interaction affects full-body movement and postural stability. Eighteen children participated in a within-subjects study involving two conditions: active interaction with a handheld tactile rhythm-matching game and a comparison condition in which they held the same device with the tactile interaction disabled. Results showed lower heart rate during active interaction, with an average reduction of 3.37 bpm (p = 0.019), and lower overall body movement, with movement decreasing by 37.6% (p = 0.002). Regional movement analyses showed the largest reductions in head, neck, and shoulder movement (44.8% reduction) and upper-limb movement (48.5% reduction). These findings suggest that brief tactile rhythm-matching interaction with a handheld device is associated with reduced acute physiological arousal and physical restlessness in children. The study provides a preliminary baseline for future work examining how tactile robotic interactions may support calmness in more demanding or stressful contexts.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1810778"},"PeriodicalIF":3.7,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13642002/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128822","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":"SkinAxis: 3D force-sensing soft robotic skins balancing touch sensitivity and impact protection for safe pHRC.","authors":"Pasquale Ferrentino, Milan Amighi, Sadegh Zouelm, Théo Le Signor, Joost Brancart, Constantin Scholz, Jeroen Didden, Jelle Vanolst, Gaël Close, Bram Vanderborght","doi":"10.3389/frobt.2026.1937934","DOIUrl":"10.3389/frobt.2026.1937934","url":null,"abstract":"<p><p>Physical human-robot collaboration (pHRC) requires robotic skins that simultaneously ensure impact safety, as established by ISO/TS 15066, and preserve touch sensitivity for delicate human interactions. Existing soft skins enhance compliance and multimodal sensing, but their design is rarely guided by a quantitative evaluation of the trade-off between touch sensitivity and impact mitigation, and systematic impact testing against ISO/TS 15066 limits is often absent. The SkinAxis modular soft robotic skin addresses this gap by embedding a compact 3D force sensor in the soft material, directly enabling touch localization, and using a material-based design that jointly optimizes quasi-static touch sensitivity and impact safety. This purpose is achieved by combining the mechanical properties of elastomeric materials, selected through dedicated mechanical tests, to identify a stiff elastomer that efficiently transfers forces to the sensor and a highly dissipative elastomer that absorbs impact energy. To highlight the trade-off achieved by the selected materials, two main designs are benchmarked: a single-material baseline and a hybrid patch with a compliant surface, a rigid load-transmission plate, and a stiff sensor support sleeve. The designs are compared in terms of quasi-static force sensitivity <math><mrow><mo>(</mo> <mrow> <msub><mrow><mi>k</mi></mrow> <mrow><mi>ε</mi></mrow> </msub> </mrow> <mo>)</mo></mrow> </math> , touch localization performance, and maximum pressure, as well as peak-force and transmitted-energy reduction efficiencies ( <math> <mrow> <msub><mrow><mi>P</mi></mrow> <mrow><mtext>max</mtext></mrow> </msub> </mrow> </math> , <math> <mrow> <msubsup><mrow><mi>η</mi></mrow> <mrow><mtext>F</mtext></mrow> <mrow><mrow><mo>(</mo> <mrow><mo>-</mo></mrow> <mo>)</mo></mrow> </mrow> </msubsup> </mrow> </math> , <math> <mrow> <msubsup><mrow><mi>η</mi></mrow> <mrow><mtext>E</mtext></mrow> <mrow><mrow><mo>(</mo> <mrow><mo>-</mo></mrow> <mo>)</mo></mrow> </mrow> </msubsup> </mrow> </math> ), measured respectively in quasi-static compression, force-indentation, and impact experiments on a human head surrogate (PILZ PRMS setup). The results demonstrate that the hybrid solution achieves higher quasi-static force sensitivity <math><mrow><mo>(</mo> <mrow> <msub><mrow><mi>k</mi></mrow> <mrow><mi>ε</mi></mrow> </msub> <mo>=</mo> <mn>0.089</mn></mrow> <mo>)</mo></mrow> </math> , a more reliable model for touch localization; it reaches 44.66% reduction in peak force and 18.95% reduction of transmitted energy under impact at cobot's operational velocity of 1 <math> <mrow> <mfrac><mrow><mi>m</mi></mrow> <mrow><mi>s</mi></mrow> </mfrac> </mrow> </math> , with a maximum transmitted pressure of 1.11 MPa in accordance with ISO/TS 15066 limits. In parallel, finite element simulations predict the forces transmitted to the embedded force sensor in quasi-static compression and impact conditions, supporting the experimental findings.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1937934"},"PeriodicalIF":3.7,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13643023/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149138759","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":"Affordance-based robot manipulation with flow matching.","authors":"Fan Zhang, Michael Gienger","doi":"10.3389/frobt.2026.1906861","DOIUrl":"10.3389/frobt.2026.1906861","url":null,"abstract":"<p><p>We present a framework for assistive robot manipulation that addresses two fundamental challenges: efficient adaptation of large-scale models for scene affordance understanding and effective learning of robot actions by grounding the visual affordance. To tackle the first challenge, we adopt a parameter-efficient prompt tuning method, prepending learnable text prompts to a frozen vision model to predict affordances, while considering spatial and semantic relationships in multi-task scenarios. For the second challenge, we propose a flow matching method, representing a robot visuomotor policy as a conditional process of flowing random waypoints to desired robot actions. We introduce a real-world dataset with 10 tasks to evaluate our approach. Experiments show our prompt tuning method achieves competitive or superior performance to other finetuning protocols across data scales, while satisfying parameter efficiency. Furthermore, flow matching yields more stable training and faster inference compared to diffusion policy; specifically, 1-step flow matching achieves comparable accuracy to 16-step DDIM while reducing inference time by roughly 85%. Our framework seamlessly unifies high-level parameter-efficient affordance representation learning with low-level flow matching policies, illustrating how explicit affordances serve as effective spatial grounding for flow-based policies. https://github.com/HRI-EU/flow_matching.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1906861"},"PeriodicalIF":3.7,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13639668/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149116618","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: Enhancing gait therapy with artificial intelligence: current trends and future prospects.","authors":"Ankit Vijayvargiya, Rajesh Kumar, Pilani Nkomozepi, Kieran Moran, Chandra Prakash","doi":"10.3389/frobt.2026.1953216","DOIUrl":"https://doi.org/10.3389/frobt.2026.1953216","url":null,"abstract":"","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1953216"},"PeriodicalIF":3.7,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13638398/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149116614","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":"Bridging stakeholder needs and technological capabilities to identify humanoid robot applications in rehabilitation: a case study in an ALS multidisciplinary care unit.","authors":"Rachele Piras, Samuele Bordini, Riccardo K Simi, Ilaria Consolo, Valentina Esposito, Claudia Cavaggion, Maddalena Feder, Maria Fossati, Giorgio Grioli, Antonio Bicchi, Christian Lunetta, Manuel G Catalano","doi":"10.3389/frobt.2026.1944029","DOIUrl":"https://doi.org/10.3389/frobt.2026.1944029","url":null,"abstract":"<p><p>The integration of assistive service robots in healthcare has gained increasing attention for its potential to support clinical workflow and patient wellbeing. However, structured methodological approaches to identify clinically relevant applications for versatile robotic platforms before clinical implementation are still lacking. Moreover, the deployment of robots in these settings is often restricted to hyper-specialized tasks. To address these challenges, this study describes a stakeholder-driven process adopting a multidisciplinary co-design approach to adapt the Alter-Ego semi-anthropomorphic robot to the needs of a multidisciplinary neurorehabilitation unit for patients with Amyotrophic Lateral Sclerosis. We combined brainstorming, focus groups with healthcare professionals, patients and caregivers, and contextual observations to identify the real unmet needs and potential applications. The engineering team assessed the technological requirements and implementation readiness of each application. The clinical and engineering teams jointly reviewed the proposal, considering clinical, ethical, and infrastructural implications. This consensus-based process resulted in 12 use cases selected for the clinical protocol corresponding to 40 planned experimental sessions including autonomous or semi-autonomous tasks, as well as teleoperated activities for assistive and rehabilitation purposes. Furthermore, an exploratory pilot evaluated a subset of selected use cases, providing feedback to refine the platform and experimental protocol. Standardized assessments provided descriptive information on perceived workload, usability, and satisfaction. Participants generally reported a positive experience and manageable workload, while task-specific feedback identified aspects requiring further refinements. Overall, this experience offers preliminary insights into how clinical needs and technological capabilities can be jointly explored, providing a basis for subsequent clinical experimentation.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1944029"},"PeriodicalIF":3.7,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13634871/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149116661","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":"LLM-Storyteller: child-guided narrative co-creation via real-time adaptive prompting and visualization with an embodied robot.","authors":"Fatimah Alali, Saad Ezzini","doi":"10.3389/frobt.2026.1882463","DOIUrl":"https://doi.org/10.3389/frobt.2026.1882463","url":null,"abstract":"<p><p>Interactive storytelling has shown great potential in supporting children's creativity. However, existing robotic storytelling systems mostly treat the robot as the primary author or lack the ability to adapt to a child's interaction state in real time. In this paper, we present LLM-Storyteller, an embodied robotic system designed for child-guided narrative co-creation. The system preserves the child's authorship by acting solely as a facilitator through adaptive prompting, which adjusts based on real-time classification of the child's interaction state. Furthermore, it closes the creative loop by transforming the child's narrated story into a personalized animated cartoon. The architecture integrates local automatic speech recognition, state detection, an adaptive Large Language Model (LLM) prompt engine using Llama 3.2, and a story-to-animation pipeline utilizing Stable Diffusion XL. We evaluated the system across 12 simulated storytelling sessions, all of them role-played by the two authors rather than by children, measuring response latency, animation generation time, interaction state distribution, and the lexical origin of the narrative. Authorship was approximated by Lexical Narrative Ownership, the share of unique content words in the finished narrative that the simulated child introduced before the robot did. This share reached 0.87 on average, and 58 of 72 robot turns followed the measured question-based response format. Together, these indicate that the narrative vocabulary originated with the child, which is evidence of facilitation rather than a semantic proof of story ownership. An internal rating of the outputs by the two authors across four dimensions gave the highest scores to follow-up question quality and the lowest to image-story alignment. All findings are bounded to prototype-level feasibility under simulated conditions, since no children took part.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1882463"},"PeriodicalIF":3.7,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13636050/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149116652","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":"Correction: Distributed environmental sensing and soil moisture gradient navigation in modular robots.","authors":"Henry Alberto Hernandez Martinez, Holman Montiel Ariza, Luis Fernando Pedraza Martinez","doi":"10.3389/frobt.2026.1987759","DOIUrl":"10.3389/frobt.2026.1987759","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.3389/frobt.2026.1895019.].</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"13 ","pages":"1987759"},"PeriodicalIF":3.7,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13635702/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149116673","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}