Biomimetic Intelligence and Robotics最新文献_第3页

Parameterization-based trajectory planning for an 8-DOF manipulator with multiple constraints

Biomimetic Intelligence and Robotics Pub Date : 2024-11-14 DOI: 10.1016/j.birob.2024.100193

Ziwu Ren, Zhongyuan Wang, Xiaohan Liu, Rui Lin

引用次数: 0

Modeling and precise tracking control of spatial bending pneumatic soft actuators 空间弯曲气动软执行器的建模和精确跟踪控制

Biomimetic Intelligence and Robotics Pub Date : 2024-11-04 DOI: 10.1016/j.birob.2024.100192

Yize Ma, Qingxiang Wu, Zehao Qiu, Yongchun Fang, Ning Sun

引用次数: 0

Design and kinematics analysis of a cable-stayed notch manipulator for transluminal endoscopic surgery 用于腔内内窥镜手术的拉索式切口机械手的设计和运动学分析

Biomimetic Intelligence and Robotics Pub Date : 2024-10-28 DOI: 10.1016/j.birob.2024.100191

Yanqiang Lei , Fuxin Du , Huajian Song , Liping Zhang

{"title":"Design and kinematics analysis of a cable-stayed notch manipulator for transluminal endoscopic surgery","authors":"Yanqiang Lei , Fuxin Du , Huajian Song , Liping Zhang","doi":"10.1016/j.birob.2024.100191","DOIUrl":"10.1016/j.birob.2024.100191","url":null,"abstract":"<div><div>The friction between the joints of the continuum manipulator with discrete joints brings great difficulties to kinematic modeling. The traditional driving wire arrangement limits the load capacity of the manipulator. A cable-stayed notch manipulator for transluminal endoscopic surgery is proposed, and a driving force coupling kinematic mode is established. The manipulator is fabricated from a superelastic Nitinol tube with bilaterally cut rectangular notches and is actuated by a stay cable. By applying the comprehensive elliptic integral solution (CEIS) for large deformation beams, the bending angle of each elastic beam is obtained, and the kinematics from the driving space to the joint space is formed. According to the bending angle of each elastic beam, the expression of the manipulator in Cartesian space can be obtained by geometric analysis. The kinematics from the joint space to the Cartesian space is established. The outer diameter of the manipulator is only 3.5 mm, and the inner diameter can reach 2 mm, allowing instruments to pass through. The maximum error of the manipulator movement is less than 5%. The load capacity of the manipulator has been verified through the stiffness experiments, and the maximum load of the manipulator can reach 400 g. The cable-stayed notch manipulator can be accurately modeled on the base of CEIS, and its motion accuracy can meet the needs of engineering applications. The compact size and excellent load capacity of the manipulator make it potential for application in transluminal endoscopic surgical robots.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"4 4","pages":"Article 100191"},"PeriodicalIF":0.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702391","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}

引用次数: 0

DS-YOLO: A dense small object detection algorithm based on inverted bottleneck and multi-scale fusion network DS-YOLO：基于倒置瓶颈和多尺度融合网络的密集小目标检测算法

Biomimetic Intelligence and Robotics Pub Date : 2024-10-26 DOI: 10.1016/j.birob.2024.100190

Hongyu Zhang , Guoliang Li , Dapeng Wan , Ziyue Wang , Jinshun Dong , Shoujun Lin , Lixia Deng , Haiying Liu

{"title":"DS-YOLO: A dense small object detection algorithm based on inverted bottleneck and multi-scale fusion network","authors":"Hongyu Zhang , Guoliang Li , Dapeng Wan , Ziyue Wang , Jinshun Dong , Shoujun Lin , Lixia Deng , Haiying Liu","doi":"10.1016/j.birob.2024.100190","DOIUrl":"10.1016/j.birob.2024.100190","url":null,"abstract":"<div><div>In the field of security, intelligent surveillance tasks often involve a large number of dense and small objects, with severe occlusion between them, making detection particularly challenging. To address this significant challenge, Dense and Small YOLO (DS-YOLO), a dense small object detection algorithm based on YOLOv8s, is proposed in this paper. Firstly, to enhance the dense small objects’ feature extraction capability of backbone network, the paper proposes a lightweight backbone. The improved C2fUIB is employed to create a lightweight model and expand the receptive field, enabling the capture of richer contextual information and reducing the impact of occlusion on detection accuracy. Secondly, to enhance the feature fusion capability of model, a multi-scale feature fusion network, Light-weight Full Scale PAFPN (LFS-PAFPN), combined with the DO-C2f module, is introduced. The new module successfully reduces the miss rate of dense small objects while ensuring the accuracy of detecting large objects. Finally, to minimize feature loss of dense objects during network transmission, a dynamic upsampling module, DySample, is implemented. DS-YOLO was trained and tested on the CrowdHuman and VisDrone2019 datasets, which contain a large number of densely populated pedestrians, vehicles and other objects. Experimental evaluations demonstrated that DS-YOLO has advantages in dense small object detection tasks. Compared with YOLOv8s, the Recall and [email protected] are increased by 4.9% and 4.2% on CrowdHuman dataset, 4.6% and 5% on VisDrone2019, respectively. Simultaneously, DS-YOLO does not introduce a substantial amount of computing overhead, maintaining low hardware requirements.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"4 4","pages":"Article 100190"},"PeriodicalIF":0.0,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552404","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}

引用次数: 0

Human autonomy teaming-based safety-aware navigation through bio-inspired and graph-based algorithms 通过生物启发和基于图的算法实现基于人类自主团队的安全意识导航

Biomimetic Intelligence and Robotics Pub Date : 2024-10-18 DOI: 10.1016/j.birob.2024.100189

Timothy Sellers , Tingjun Lei , Chaomin Luo , Zhuming Bi , Gene Eu Jan

{"title":"Human autonomy teaming-based safety-aware navigation through bio-inspired and graph-based algorithms","authors":"Timothy Sellers , Tingjun Lei , Chaomin Luo , Zhuming Bi , Gene Eu Jan","doi":"10.1016/j.birob.2024.100189","DOIUrl":"10.1016/j.birob.2024.100189","url":null,"abstract":"<div><div>In the field of autonomous robots, achieving complete precision is challenging, underscoring the need for human intervention, particularly in ensuring safety. Human Autonomy Teaming (HAT) is crucial for promoting safe and efficient human–robot collaboration in dynamic indoor environments. This paper introduces a framework designed to address these precision gaps, enhancing safety and robotic interactions within such settings. Central to our approach is a hybrid graph system that integrates the Generalized Voronoi Diagram (GVD) with spatio-temporal graphs, effectively combining human feedback, environmental factors, and key waypoints. An integral component of this system is the improved Node Selection Algorithm (iNSA), which utilizes the revised Grey Wolf Optimization (rGWO) for better adaptability and performance. Furthermore, an obstacle tracking model is employed to provide predictive data, enhancing the efficiency of the system. Human insights play a critical role, from supplying initial environmental data and determining key waypoints to intervening during unexpected challenges or dynamic environmental changes. Extensive simulation and comparison tests confirm the reliability and effectiveness of our proposed model, highlighting its unique advantages in the domain of HAT. This comprehensive approach ensures that the system remains robust and responsive to the complexities of real-world applications.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"4 4","pages":"Article 100189"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142702506","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}

引用次数: 0

Design of FDM-printable tendon-driven continuum robots using a serial S-shaped backbone structure

Biomimetic Intelligence and Robotics Pub Date : 2024-10-18 DOI: 10.1016/j.birob.2024.100188

Kaidi Zhu, Tim C. Lueth, Yilun Sun

引用次数: 0

Editorial for the special issue on bio-inspired robotic dexterity intelligence 为生物启发机器人灵巧智能特刊撰写社论

Biomimetic Intelligence and Robotics Pub Date : 2024-10-16 DOI: 10.1016/j.birob.2024.100186

Qiang Li, Shuo Wang, Cong Wang, Jihong Zhu

引用次数: 0

Leveraging large language models for comprehensive locomotion control in humanoid robots design 在仿人机器人设计中利用大型语言模型实现综合运动控制

Biomimetic Intelligence and Robotics Pub Date : 2024-10-16 DOI: 10.1016/j.birob.2024.100187

Shilong Sun , Chiyao Li , Zida Zhao , Haodong Huang , Wenfu Xu

引用次数: 0

LQR-based control strategy for improving human–robot companionship and natural obstacle avoidance 基于 LQR 的控制策略，改善人机陪伴和自然避障能力

Biomimetic Intelligence and Robotics Pub Date : 2024-10-04 DOI: 10.1016/j.birob.2024.100185

Zefan Su , Hanchen Yao , Jianwei Peng , Zhelin Liao , Zengwei Wang , Hui Yu , Houde Dai , Tim C. Lueth

{"title":"LQR-based control strategy for improving human–robot companionship and natural obstacle avoidance","authors":"Zefan Su , Hanchen Yao , Jianwei Peng , Zhelin Liao , Zengwei Wang , Hui Yu , Houde Dai , Tim C. Lueth","doi":"10.1016/j.birob.2024.100185","DOIUrl":"10.1016/j.birob.2024.100185","url":null,"abstract":"<div><div>In the dynamic and unstructured environment of human–robot symbiosis, companion robots require natural human–robot interaction and autonomous intelligence through multimodal information fusion to achieve effective collaboration. Nevertheless, the control precision and coordination of the accompanying actions are not satisfactory in practical applications. This is primarily attributed to the difficulties in the motion coordination between the accompanying target and the mobile robot. This paper proposes a companion control strategy based on the Linear Quadratic Regulator (LQR) to enhance the coordination and precision of robot companion tasks. This method enables the robot to adapt to sudden changes in the companion target’s motion. Besides, the robot could smoothly avoid obstacles during the companion process. Firstly, a human–robot companion interaction model based on nonholonomic constraints is developed to determine the relative position and orientation between the robot and the companion target. Then, an LQR-based companion controller incorporating behavioral dynamics is introduced to simultaneously avoid obstacles and track the companion target’s direction and velocity. Finally, various simulations and real-world human–robot companion experiments are conducted to regulate the relative position, orientation, and velocity between the target object and the robot platform. Experimental results demonstrate the superiority of this approach over conventional control algorithms in terms of control distance and directional errors throughout system operation. The proposed LQR-based control strategy ensures coordinated and consistent motion with target persons in social companion scenarios.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"4 4","pages":"Article 100185"},"PeriodicalIF":0.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572802","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}

引用次数: 0

Predictive modeling of flexible EHD pumps using Kolmogorov–Arnold Networks 利用 Kolmogorov-Arnold 网络建立柔性 EHD 泵的预测模型

Biomimetic Intelligence and Robotics Pub Date : 2024-09-17 DOI: 10.1016/j.birob.2024.100184

Yanhong Peng , Yuxin Wang , Fangchao Hu , Miao He , Zebing Mao , Xia Huang , Jun Ding

引用次数: 0