Biomimetic Intelligence and Robotics最新文献

{"title":"Exoskeletons in the context of soldiers: Current status and future research trends","authors":"Xinmeng Ma ,&nbsp;Lingfeng Lv ,&nbsp;Weipeng Liu ,&nbsp;Feng Niu ,&nbsp;Haihang Wang ,&nbsp;Haoyu Wang ,&nbsp;Libin Zhao ,&nbsp;Zihao Wang ,&nbsp;Zhipu Wang","doi":"10.1016/j.birob.2025.100254","DOIUrl":"10.1016/j.birob.2025.100254","url":null,"abstract":"<div><div>Modern military drills and conventional training, performed under all-weather conditions, impose exacting challenges on soldiers. This has motivated the development of exoskeleton robot systems, leveraging advanced technology and material innovation. These systems have demonstrated their effectiveness at assisting movement, enhancing protection, promoting rehabilitation, and providing comprehensive support to soldiers. This groundbreaking technology not only reduces a soldier’s physical exertion significantly but also effectively diminishes the risk of injury during training, infusing new vitality into the enhancement of military capabilities. Different types of exoskeleton robots differ in their focus. Lower-limb exoskeleton robots are designed to increase the soldier’s endurance. Upper-limb exoskeleton robots enhance strength. This paper provides a detailed explanation of the key technologies of various types of exoskeleton robots, covering their mechanical design, electromechanical transmission structures, sensors, and actuation methods. It also explores the diverse application scenarios of exoskeleton robots in the military field, systematically introducing their development trajectory, milestone achievements, and the cutting-edge technologies currently employed, as well as the challenges faced. The conclusion offers a prospective discussion of future development pathways, anticipating the broad prospects for exoskeleton robots in the military domain.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 3","pages":"Article 100254"},"PeriodicalIF":5.4,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wheeled-legged robots for multi-terrain locomotion in plateau environments","authors":"Kang Wang ,&nbsp;Jinmian Hou ,&nbsp;Shichao Zhou ,&nbsp;Dachuang Wei ,&nbsp;Wei Xu ,&nbsp;Yulin Wang ,&nbsp;Hui Chai ,&nbsp;Lingkun Chen ,&nbsp;Qiuguo Zhu ,&nbsp;Liang Gao ,&nbsp;Min Guo ,&nbsp;Guoteng Zhang ,&nbsp;Zhongqu Xie ,&nbsp;Tuo Liu ,&nbsp;Mingyue Zhu ,&nbsp;Yueming Wang ,&nbsp;Tong Yan ,&nbsp;Jingsong Gao ,&nbsp;Meng Hong ,&nbsp;Weikai Ding","doi":"10.1016/j.birob.2025.100256","DOIUrl":"10.1016/j.birob.2025.100256","url":null,"abstract":"<div><div>Wheeled-legged robots integrate the mobility efficiency of wheeled platforms with the terrain adaptability of legged robots, making them ideal for complex, unstructured environments. However, balancing high payload capacity with agile multimodal locomotion remains a major challenge. This paper presents a field study conducted in the high-altitude region of Golmud, Qinghai, with elevations ranging from 2800 m to 4000 m. We evaluate three wheeled-legged robot platforms of different scales on diverse terrains including Gobi, desert, grassland, and wetlands. Our experiments demonstrate the robot’s robust locomotion performance across multimodal tasks such as obstacle crossing, slope climbing, and terrain classification. Moreover, we validate the performance of autonomous perception systems, including real-time localization and 3D mapping, under harsh plateau conditions. The results provide valuable insights into the deployment of wheeled-legged robots in extreme natural environments and lay a solid foundation for future applications in inspection, rescue, and transport missions in high-altitude regions.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 3","pages":"Article 100256"},"PeriodicalIF":5.4,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kirigami analogies for parallelogram-based remote-center-of-motion mechanisms","authors":"Bok Seng Yeow ,&nbsp;Alex Wang ,&nbsp;Chin-Hsing Kuo ,&nbsp;Hongliang Ren","doi":"10.1016/j.birob.2025.100251","DOIUrl":"10.1016/j.birob.2025.100251","url":null,"abstract":"<div><div>This paper presents a framework for applying origami-kirigami techniques to design kirigami analogies for remote center-of-motion (RCM) mechanisms, specifically targeting minimally invasive keyhole procedures. The proposed kirigami RCM analogs emulate the motions of existing bar-linkage RCMs, offering advantages in deployability, transportability, and simplified fabrication. A workflow is introduced to transition from initial crease patterns to functional kirigami equivalents, demonstrating the potential for customizability and scalability. Furthermore, a proof-of-concept kirigami RCM under magnetic actuation is presented, showcasing its ability to reduce structural profile during transportation and improve device deployment. Three representative parallelogram-based RCM mechanisms: coupled dual parallelogram, back-drivable, and triple parallelogram, are transformed into kirigami analogs, highlighting the versatility of the design approach. The discussion includes computational modeling, fabrication considerations, and potential applications in MIS robots. This work contributes to the development of compact, deployable, and cost-effective RCM mechanisms for robotic keyhole procedures. This approach can also further facilitate the education of RCM mechanisms and the hands-on demonstration of small-scale RCM concepts.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 3","pages":"Article 100251"},"PeriodicalIF":5.4,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Literature survey on machine learning techniques for enhancing accuracy of myoelectric hand gesture recognition in real-world prosthetic hand control","authors":"Hongquan Le ,&nbsp;Marc in Het Panhuis ,&nbsp;Gursel Alici","doi":"10.1016/j.birob.2025.100250","DOIUrl":"10.1016/j.birob.2025.100250","url":null,"abstract":"<div><div>The human hand, essential for performing daily tasks and facilitating social interaction, is indispensable to everyday life. Millions worldwide experience varying levels of amputation, profoundly affecting their physical, emotional, and psychological well-being, limiting independence, and reducing quality of life. Myoelectric prosthetics, the most advanced active prosthetic hands, use surface electromyography (sEMG) signals and pattern recognition to translate user intentions into control signals. Despite these advancements, high rejection rates persist due to the non-stationarity of sEMG signals, leading to inconsistent and often frustrating user experiences. As a result, clinical and academic research has increasingly focused on improving myoelectric hand gesture recognition under real-world conditions to reduce rejection rates and enhance user acceptance of myoelectric prostheses. Given the vast and diverse range of methods applied in previous research, this survey aims to systematically highlight key studies and provide an overview of the field’s current achievements. Furthermore, research on machine learning for myoelectric hand gesture recognition has been largely influenced by unrelated fields of computer science, such as computer vision and natural language processing. However, myoelectric hand gesture recognition presents unique challenges, particularly severe and unpredictable covariate shifts in sEMG signals, which require specialized approaches. To address these challenges, we propose a new taxonomy for categorizing machine learning models based on feature extraction methods and decision boundary strategies. Additionally, this paper highlights the need for benchmark datasets that accurately reflect real-world conditions and emphasizes the importance of re-evaluating real-time performance, particularly when using long temporal contextual windows. This study concludes with research challenges and future research directions to enhance the accuracy of myoelectric hand gesture recognition using machine learning techniques.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 3","pages":"Article 100250"},"PeriodicalIF":5.4,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Snake-inspired trajectory planning and control for confined pipeline inspection with hyper-redundant manipulators","authors":"Junjie Zhu ,&nbsp;Mingming Su ,&nbsp;Longchuan Li ,&nbsp;Yuxuan Xiang ,&nbsp;Jianming Wang ,&nbsp;Xuan Xiao","doi":"10.1016/j.birob.2025.100245","DOIUrl":"10.1016/j.birob.2025.100245","url":null,"abstract":"<div><div>The hyper-redundant manipulator (HRM) can explore narrow and curved pipelines by leveraging its high flexibility and redundancy. However, planning collision-free motion trajectories for HRMs in confined environments remains a significant challenge. To address this issue, a pipeline inspection approach that combines nonlinear model predictive control (NMPC) with the snake-inspired crawling algorithm(SCA) is proposed. The approach consists of three processes: insertion, inspection, and exit. The insertion and exit processes utilize the SCA, inspired by snake motion, to significantly reduce path planning time. The inspection process employs NMPC to generate collision-free motion. The prototype HRM is developed, and inspection experiments are conducted in various complex pipeline scenarios to validate the effectiveness and feasibility of the proposed method. Experimental results demonstrate that the approach effectively minimizes the computational cost of path planning, offering a practical solution for HRM applications in pipeline inspection.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 3","pages":"Article 100245"},"PeriodicalIF":5.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic Informed Trees (GIT*): Path planning via reinforced genetic programming heuristics","authors":"Liding Zhang ,&nbsp;Kuanqi Cai ,&nbsp;Zhenshan Bing ,&nbsp;Chaoqun Wang ,&nbsp;Alois Knoll","doi":"10.1016/j.birob.2025.100237","DOIUrl":"10.1016/j.birob.2025.100237","url":null,"abstract":"<div><div>Optimal path planning involves finding a feasible state sequence between a start and a goal that optimizes an objective. This process relies on heuristic functions to guide the search direction. While a robust function can improve search efficiency and solution quality, current methods often overlook available environmental data and simplify the function structure due to the complexity of information relationships. This study introduces Genetic Informed Trees (GIT*), which improves upon Effort Informed Trees (EIT*) by integrating a wider array of environmental data, such as repulsive forces from obstacles and the dynamic importance of vertices, to refine heuristic functions for better guidance. Furthermore, we integrated reinforced genetic programming (RGP), which combines genetic programming with reward system feedback to mutate genotype-generative heuristic functions for GIT*. RGP leverages a multitude of data types, thereby improving computational efficiency and solution quality within a set timeframe. Comparative analyses demonstrate that GIT* surpasses existing single-query, sampling-based planners in problems ranging from <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>4</mn></mrow></msup></math></span> to <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>16</mn></mrow></msup></math></span> and was tested on a real-world mobile manipulation task. A video showcasing our experimental results is available at <span><span>https://youtu.be/URjXbc_BiYg</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 3","pages":"Article 100237"},"PeriodicalIF":5.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144892904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image segmentation network for laparoscopic surgery","authors":"Kang Peng ,&nbsp;Yaoyuan Chang ,&nbsp;Guodong Lang ,&nbsp;Jian Xu ,&nbsp;Yongsheng Gao ,&nbsp;Jiajun Yin ,&nbsp;Jie Zhao","doi":"10.1016/j.birob.2025.100236","DOIUrl":"10.1016/j.birob.2025.100236","url":null,"abstract":"<div><div>Surgical image segmentation serves as the foundation for laparoscopic surgical navigation technology. The indistinct local features of biological tissues in laparoscopic image pose challenges for image segmentation. To address this issue, we develop an image segmentation network tailored for laparoscopic surgery. Firstly, we introduce the Mixed Attention Enhancement (MAE) module that sequentially conducts the Channel Attention Enhancement (CAE) module and the Global Feature Enhancement (GFE) module linked in series. The CAE module enhances the network’s perception of prominent channels, allowing feature maps to exhibit clear local features. The GFE module is capable of extracting global features from both the height and width dimensions of images and integrating them into three-dimensional features. This enhancement improves the network’s ability to capture global features, thereby facilitating the inference of regions with indistinct local features. Secondly, we propose the Multi-scale Feature Fusion (MFF) module. This module expands the feature map into various scales, further enlarging the network’s receptive field and enhancing perception of features at multiple scales. In addition, we tested the proposed network on the EndoVis 2018 and a human minimally invasive liver resection image segmentation dataset, comparing it against six other advanced image segmentation networks. The comparative test results demonstrate that the proposed network achieves the most advanced performance on both datasets, proving its potential in improving surgical image segmentation outcome. The codes of MAMNet are available at: <span><span>https://github.com/Pang1234567/MAMNet</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 3","pages":"Article 100236"},"PeriodicalIF":0.0,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144490238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An adaptive compensation strategy for sensors based on the degree of degradation","authors":"Yanbin Li ,&nbsp;Wei Zhang ,&nbsp;Zhiguo Zhang ,&nbsp;Xiaogang Shi ,&nbsp;Ziruo Li ,&nbsp;Mingming Zhang ,&nbsp;Wenzheng Chi","doi":"10.1016/j.birob.2025.100235","DOIUrl":"10.1016/j.birob.2025.100235","url":null,"abstract":"<div><div>Simultaneous Localization and Mapping (SLAM) is widely used to solve the localization problem of unmanned devices such as robots. However, in degraded environments, the accuracy of SLAM is greatly reduced due to the lack of constrained features. In this article, we propose a deep learning-based adaptive compensation strategy for sensors. First, we create a dataset dedicated to training a degradation detection model, which contains coordinate data of particle swarms with different distributional features, and endow the model with degradation detection capability through supervised learning. Second, we design a lightweight network model with short computation time and good accuracy for real-time degradation detection tasks. Finally, an adaptive compensation strategy for sensors based on the degree of degradation is designed, where the SLAM is able to assign different weights to the sensor information according to the degree of degradation given by the model, to adjust the contribution of different sensors in the pose optimization process. We demonstrate through simulation experiments and real experiments that the robustness of the improved SLAM in degraded environments is significantly enhanced, and the accuracy of localization and mapping are improved.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 4","pages":"Article 100235"},"PeriodicalIF":5.4,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145266328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tendon friction compensation and slack avoidance for trajectory tracking control of the tendon-driven medical continuum manipulator","authors":"Pengyu Du ,&nbsp;Jianxiong Hao ,&nbsp;Kun Qian ,&nbsp;Yue Zhang ,&nbsp;Zhiqiang Zhang ,&nbsp;Chaoyang Shi","doi":"10.1016/j.birob.2025.100234","DOIUrl":"10.1016/j.birob.2025.100234","url":null,"abstract":"<div><div>Tendon-driven continuum manipulators can perform tasks in confined environments due to their flexibility and curvilinearity, especially in minimally invasive surgeries. However, the friction along tendons and tendon slack present challenges to their motion control. This work proposes a trajectory tracking controller based on adaptive fuzzy sliding mode control (AFSMC) for the tendon-driven continuum manipulators. It consists of a sliding mode control (SMC) law with two groups of adaptive fuzzy subcontrollers. The first one is utilized to estimate and compensate for friction forces along tendons. The second one adapts the switching terms of SMC to alleviate the chattering phenomenon and enhance control robustness. To prevent tendon slack, an antagonistic strategy along with the AFSMC controller is adopted to allocate driving forces. Simulation and experiment studies have been conducted to investigate the efficacy of the proposed controller. In free space experiments, the AFSMC controller generates an average root-mean-square error (RMSE) of 0.42% compared with 0.90% of the SMC controller. In the case of a 50 g load, the proposed controller reduces the average RMSE to 1.47% compared with 4.29% of the SMC controller. These experimental results demonstrate that the proposed AFSMC controller has high control accuracy, robustness, and reduced chattering.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 4","pages":"Article 100234"},"PeriodicalIF":5.4,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel 3D instrument navigation in intracranial vascular surgery with multi-source image fusion and self-calibration","authors":"Linsen Zhang ,&nbsp;Shiqi Liu ,&nbsp;Xiaoliang Xie ,&nbsp;Xiaohu Zhou ,&nbsp;Zengguang Hou ,&nbsp;Xinkai Qu ,&nbsp;Wenzheng Han ,&nbsp;Meng Song ,&nbsp;Xiyao Ma ,&nbsp;Haining Zhao","doi":"10.1016/j.birob.2025.100233","DOIUrl":"10.1016/j.birob.2025.100233","url":null,"abstract":"<div><div>In cerebrovascular interventional surgery, spatial position prediction navigation (SPPN) provides 3D spatial information of the vascular lumen, reducing the spatial dimension loss from digital subtraction angiography (DSA) and improving surgical precision. However, it is limited in its adaptability to complex vascular environments and prone to error accumulation. To address these issues, we propose spatial position prediction-based multimodal navigation (SPPMN), integrating minimal intraoperative X-ray images to enhance SPPN accuracy. In the first phase, a feature-weighted dynamic time warping (FDTW)-based branch matching algorithm is introduced for 3D topological positioning under non-registered conditions, with a dynamic location repositioning module for real-time corrections. In the second phase, an occlusion correction module, based on the elastic potential energy of the instrument tip, dynamically adjusts the tip’s angle to achieve low-projection occlusion control. Experimental validation using a high-precision electromagnetic tracking system (EMTS) on a 3D vascular model shows that the proposed method achieves an average 3D positioning accuracy of 9.36 mm in intracranial vascular regions, with a 78% reduction in radiation exposure, significantly enhancing both precision and safety in interventional surgeries.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 3","pages":"Article 100233"},"PeriodicalIF":5.4,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}