Biomimetic Intelligence and Robotics最新文献_第2页

Learning-based robot assembly method for peg insertion tasks on inclined hole using time-series force information

Biomimetic Intelligence and Robotics Pub Date : 2025-01-05 DOI: 10.1016/j.birob.2024.100209

Zhifei Shen , Zhiyong Jiang , Jingwang Zhang , Jun Wu , Qiuguo Zhu

引用次数: 0

Motion planning for robotics: A review for sampling-based planners

Biomimetic Intelligence and Robotics Pub Date : 2025-01-04 DOI: 10.1016/j.birob.2024.100207

Liding Zhang , Kuanqi Cai , Zewei Sun , Zhenshan Bing , Chaoqun Wang , Luis Figueredo , Sami Haddadin , Alois Knoll

{"title":"Motion planning for robotics: A review for sampling-based planners","authors":"Liding Zhang , Kuanqi Cai , Zewei Sun , Zhenshan Bing , Chaoqun Wang , Luis Figueredo , Sami Haddadin , Alois Knoll","doi":"10.1016/j.birob.2024.100207","DOIUrl":"10.1016/j.birob.2024.100207","url":null,"abstract":"<div><div>Recent advancements in robotics have transformed industries such as manufacturing, logistics, surgery, and planetary exploration. A key challenge is developing efficient motion planning algorithms that allow robots to navigate complex environments while avoiding collisions and optimizing metrics like path length, sweep area, execution time, and energy consumption. Among the available algorithms, sampling-based methods have gained the most traction in both research and industry due to their ability to handle complex environments, explore free space, and offer probabilistic completeness along with other formal guarantees. Despite their widespread application, significant challenges still remain. To advance future planning algorithms, it is essential to review the current state-of-the-art solutions and their limitations. In this context, this work aims to shed light on these challenges and assess the development and applicability of sampling-based methods. Furthermore, we aim to provide an in-depth analysis of the design and evaluation of ten of the most popular planners across various scenarios. Our findings highlight the strides made in sampling-based methods while underscoring persistent challenges. This work offers an overview of the important ongoing research in robotic motion planning.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 1","pages":"Article 100207"},"PeriodicalIF":0.0,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151589","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

A hybrid artificial bee colony algorithm with genetic augmented exploration mechanism toward safe and smooth path planning for mobile robot

Biomimetic Intelligence and Robotics Pub Date : 2024-12-26 DOI: 10.1016/j.birob.2024.100206

Fan Ye , Peng Duan , Leilei Meng , Lingyan Xue

{"title":"A hybrid artificial bee colony algorithm with genetic augmented exploration mechanism toward safe and smooth path planning for mobile robot","authors":"Fan Ye , Peng Duan , Leilei Meng , Lingyan Xue","doi":"10.1016/j.birob.2024.100206","DOIUrl":"10.1016/j.birob.2024.100206","url":null,"abstract":"<div><div>Path planning is important for mobile robot to ensure safe and efficient navigation. This paper proposes a hybrid artificial bee colony with genetic augmented exploration mechanism (HABC-GA) that enables mobile robot to achieve safe and smooth path planning. Considering the characteristics of path planning problem, a mathematical model is constructed to balance three objectives: path length, path safety, and path smoothness. In the employed bee phase, a genetic augmented exploration mechanism is designed, which encompasses redesigned path crossover, adaptive obstacle-aware mutation, and dynamic elite selection operators. In the onlooker bee phase, an objective-guided optimization strategy is investigated to improve local search ability. In the scout bee phase, a dual exploration restart strategy is developed to increase the activity of individuals in the population, in which stagnant individuals in the evolution are replaced by more promising ones. Finally, the proposed HABC-GA is compared with five efficient algorithms in 24 instances of six representative environments. Simulation results demonstrate the effectiveness and high performance of HABC-GA in obtaining safe and smooth paths.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 2","pages":"Article 100206"},"PeriodicalIF":0.0,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143160557","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

Using neuroevolution for designing soft medical devices

Biomimetic Intelligence and Robotics Pub Date : 2024-12-19 DOI: 10.1016/j.birob.2024.100205

Hugo Alcaraz-Herrera , Michail-Antisthenis Tsompanas , Igor Balaz , Andrew Adamatzky

引用次数: 0

Review of bioinspired aquatic jumping robots

Biomimetic Intelligence and Robotics Pub Date : 2024-12-13 DOI: 10.1016/j.birob.2024.100204

Tao Zhang , Jiawei Dong , Qianqian Chen , Xiongqian Wu , Shuqi Wang , Yisheng Guan

引用次数: 0

A survey of autonomous robots and multi-robot navigation: Perception, planning and collaboration

Biomimetic Intelligence and Robotics Pub Date : 2024-12-07 DOI: 10.1016/j.birob.2024.100203

Weinan Chen , Wenzheng Chi , Sehua Ji , Hanjing Ye , Jie Liu , Yunjie Jia , Jiajie Yu , Jiyu Cheng

引用次数: 0

A survey on the visual perception of humanoid robot

Biomimetic Intelligence and Robotics Pub Date : 2024-11-26 DOI: 10.1016/j.birob.2024.100197

Teng Bin , Hanming Yan , Ning Wang , Milutin N. Nikolić , Jianming Yao , Tianwei Zhang

引用次数: 0

A fast registration method for multi-view point clouds with low overlap in robotic measurement

Biomimetic Intelligence and Robotics Pub Date : 2024-11-26 DOI: 10.1016/j.birob.2024.100195

Chuangchuang Li , Xubin Lin , Zhaoyang Liao , Hongmin Wu , Zhihao Xu , Xuefeng Zhou

{"title":"A fast registration method for multi-view point clouds with low overlap in robotic measurement","authors":"Chuangchuang Li , Xubin Lin , Zhaoyang Liao , Hongmin Wu , Zhihao Xu , Xuefeng Zhou","doi":"10.1016/j.birob.2024.100195","DOIUrl":"10.1016/j.birob.2024.100195","url":null,"abstract":"<div><div>With the rapid advancement of mechanical automation and intelligent processing technology, accurately measuring the surfaces of complex parts has emerged as a significant research challenge. Robotic measurement technology plays a crucial role in facilitating rapid quality inspections during the manufacturing process due to its inherent flexibility. However, the irregular shapes and viewpoint occlusions of complex parts complicate precise measurement. To address these challenges, this work proposes a point cloud registration network for robotic scanning systems and introduces a DBR-Net (Dual-line Registration Network) to overcome the issues of low overlap rates and perspective occlusion that currently impede the registration of certain workpieces. First, feature extraction is performed using a bilinear encoder and multi-level feature interactions of both point-wise and global features. Subsequently, the features are sampled through unanimous voting and fed into the RANSAC (Random Sample Consensus) algorithm for pose estimation, enabling multi-view point cloud registration. Experimental results demonstrate that this method significantly outperforms many existing techniques in terms of feature extraction and registration accuracy, thereby enhancing the overall performance of point cloud registration.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 2","pages":"Article 100195"},"PeriodicalIF":0.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143160558","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

Legged odometry based on fusion of leg kinematics and IMU information in a humanoid robot

Biomimetic Intelligence and Robotics Pub Date : 2024-11-25 DOI: 10.1016/j.birob.2024.100196

Huailiang Ma , Aiguo Song , Jingwei Li , Ligang Ge , Chunjiang Fu , Guoteng Zhang

引用次数: 0

Interaction model estimation-based robotic force-position coordinated optimization for rigid–soft heterogeneous contact tasks

Biomimetic Intelligence and Robotics Pub Date : 2024-11-19 DOI: 10.1016/j.birob.2024.100194

Haochen Zheng , Xueqian Zhai , Hongmin Wu , Jia Pan , Zhihao Xu , Xuefeng Zhou

{"title":"Interaction model estimation-based robotic force-position coordinated optimization for rigid–soft heterogeneous contact tasks","authors":"Haochen Zheng , Xueqian Zhai , Hongmin Wu , Jia Pan , Zhihao Xu , Xuefeng Zhou","doi":"10.1016/j.birob.2024.100194","DOIUrl":"10.1016/j.birob.2024.100194","url":null,"abstract":"<div><div>Inspired by Model Predictive Interaction Control (MPIC), this paper proposes differential models for estimating contact geometric parameters and normal-friction forces and formulates an optimal control problem with multiple constraints to allow robots to perform rigid–soft heterogeneous contact tasks. Within the MPIC, robot dynamics are linearized, and Extended Kalman Filters are used for the online estimation of geometry-aware parameters. Meanwhile, a geometry-aware Hertz contact model is introduced for the online estimation of contact forces. We then implement the force-position coordinate optimization by incorporating the contact parameters and interaction force constraints into a gradient-based optimization MPC. Experimental validations were designed for two contact modes: “single-point contact” and “continuous contact”, involving materials with four different Young’s moduli and tested in human arm “relaxation–contraction” task. Results indicate that our framework ensures consistent geometry-aware parameter estimation and maintains reliable force interaction to guarantee safety. Our method reduces the maximum impact force by 50% and decreases the average force error by 42%. The proposed framework has potential applications in medical and industrial tasks involving the manipulation of rigid, soft, and deformable objects.</div></div>","PeriodicalId":100184,"journal":{"name":"Biomimetic Intelligence and Robotics","volume":"5 1","pages":"Article 100194"},"PeriodicalIF":0.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151592","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