2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)最新文献_第9页

Prediction of Loss-of-Balance of the Human Based on Plantar Pressure by Using the SA-RF Algorithm 利用 SA-RF 算法根据足底压力预测人体失去平衡的情况

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2023-12-04 DOI: 10.1109/ROBIO58561.2023.10354936

Liangjie Tu, Fugang Yi, Bingfei Fan, Mingyu Du, Shibo Cai

{"title":"Prediction of Loss-of-Balance of the Human Based on Plantar Pressure by Using the SA-RF Algorithm","authors":"Liangjie Tu, Fugang Yi, Bingfei Fan, Mingyu Du, Shibo Cai","doi":"10.1109/ROBIO58561.2023.10354936","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354936","url":null,"abstract":"Elderly people are easy to suffer from accidental injuries due to loss-of-balance in daily life. Wearable sensing technology is promising for detecting or predicting loss-of-balance events. This paper proposes a human loss-of-balance prediction method based on a customized wearable plantar pressure sensing system. To realize accurate prediction of loss-of-balance, we integrate the simulated annealing algorithm (SA) and the random forest algorithm (RF) to construct a SA-RF prediction model, where the input of the model is the plantar pressure data of the feet and the output of the model is the label of the human motion state. To validate the effectiveness of the proposed SA-RF model, 15 healthy subjects participated in the experiments. The experimental results show that the classification and recognition accuracy of the SA-RF model are significantly improved compared to the RF model, especially for the recognition of the easily loss-of-balance state. The accuracy of the proposed SA-RF model reaches 90%, which is a 5% improvement compared to the RF model. Therefore, the use of the SA-RF model based on plantar pressure can effectively predict loss-of-balance and thus has the potential to be integrated into fall prevention applications.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"64 6","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187001","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}

引用次数: 0

Learning Stall Recovery Policies using a Soft Actor-Critic Algorithm with Smooth Reward Functions 利用具有平滑奖励函数的软代理批判算法学习失速恢复策略

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2023-12-04 DOI: 10.1109/ROBIO58561.2023.10354940

Junqiu Wang, Jianmei Tan, Peng Lin, Chenguang Xing, Bo Liu

{"title":"Learning Stall Recovery Policies using a Soft Actor-Critic Algorithm with Smooth Reward Functions","authors":"Junqiu Wang, Jianmei Tan, Peng Lin, Chenguang Xing, Bo Liu","doi":"10.1109/ROBIO58561.2023.10354940","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354940","url":null,"abstract":"We propose an effective stall recovery learning approach based on a soft actor-critic algorithm with smooth reward functions. Stalling is extremely dangerous for aircraft and unmanned aerial vehicles (UAVs) because altitude decreases can result in fatal accidents. Stall recovery policies perform appropriate control sequences to save aircrafts from such lethal situations. Learning stall recovery policies using reinforcement learning methods is desirable because such policies can be learned automatically. However, stall recovery training is challenging since the interplay between an aircraft and its environment is very complicated. In this work, the proposed stall recovery learning approach yields better performance than other methods. We successfully apply smooth reward functions to the learning process because reward functions are critical for the convergence of policy learning. We achieve good performance by applying reward scaling to the soft actor-critic algorithm with automatic entropy learning. Experimental results demonstrate that stalls can be successfully recovered using the learned policies. The comparison results show that our method provides better results than previous algorithms.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"64 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187005","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}

引用次数: 0

A Sample Repetitive Manipulation Mechanism (SRMM) for Lunar Regolith In-Situ Analysis: Design and Validation 用于月球岩石原位分析的样品重复操纵装置（SRMM）：设计与验证

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2023-12-04 DOI: 10.1109/ROBIO58561.2023.10354957

Yi Liu, Junyue Tang, Yafang Liu, Gongbo Ma, Feng Sun, Ye Li, Shengyuan Jiang

{"title":"A Sample Repetitive Manipulation Mechanism (SRMM) for Lunar Regolith In-Situ Analysis: Design and Validation","authors":"Yi Liu, Junyue Tang, Yafang Liu, Gongbo Ma, Feng Sun, Ye Li, Shengyuan Jiang","doi":"10.1109/ROBIO58561.2023.10354957","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354957","url":null,"abstract":"To exactly detect the water ice of the South Pole of the moon, a lunar regolith in-situ analysis payload deploying a mass spectrometer is proposed for China future lunar exploration missions. In order to receive the lunar regolith sample from a robotic arm with a soil sampler and transfer it into a furnace for further analysis, a sample manipulation mechanism is required during the above work flow. To solve the problems of adapting the sampler’s docking accuracy, receiving and transferring two different types of lunar soil sample under times of in-situ analysis, etc., a sample repetitive manipulation mechanism (SRMM) is proposed in this paper. By using a floating adjustable docking components and a flexible hopper, two types of encapsulated regolith sample and bulk material sample can be received with minimal sample loss, respectively. In order to receive and transfer two types of samples multiple times, two sample receiving methods have been designed that can be repeatedly transferred. A worm and worm wheel combined with a ball screw is designed in SRMM. To verify the above mechanism design, validation experiments were conducted. It indicates that this novel SRMM can be deployed in the future mission after further environmental tests.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"41 5","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187206","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}

引用次数: 0

Stroke Synchronization of Underwater Modular Robot through Physical Interaction 通过物理交互实现水下模块机器人的行程同步

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2023-12-04 DOI: 10.1109/ROBIO58561.2023.10354986

Kohei Nishikawa, Y. Origane, Daisuke Kurabayashi

{"title":"Stroke Synchronization of Underwater Modular Robot through Physical Interaction","authors":"Kohei Nishikawa, Y. Origane, Daisuke Kurabayashi","doi":"10.1109/ROBIO58561.2023.10354986","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354986","url":null,"abstract":"Modular robots are expected to be used in extreme environments owing to their adaptability, and various modular robots have been developed. Most studies have focused on the expandability of capabilities or the integration of modules, whereas only a few studies have investigated autonomous decentralized control, in which each module harmonizes its own movements for overall functionality. We developed an underwater modular robot that synchronizes its paddle strokes; the robot is based on the motif of Gonium, a multicellular alga. We built a reduced system model of modules to represent the state of an oscillator by using a phase with attractive interactions with others. Because the model is similar to the Kuramoto model, we applied analysis methods. Real robotic modules were built, and experiments were conducted using a colony of the modules. The experimental results confirmed that the colony exhibited stroke synchronization ability by compensating for individual differences. The stroke synchronization is expected to stabilize the movements of robot colonies and improve their overall propulsion.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"51 8","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187224","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}

引用次数: 0

A soft hydraulic endorectal actuator for prostate radiotherapy 用于前列腺放射治疗的软液压肛门直肠内推杆

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2023-12-04 DOI: 10.1109/ROBIO58561.2023.10355037

Aryan Niknam Maleki, Alexander Thompson, M. Runciman, Julia Murray, G. Mylonas

引用次数: 0

DynGraspVS: Servoing Aided Grasping for Dynamic Environments DynGraspVS：为动态环境提供伺服辅助抓取功能

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2023-12-04 DOI: 10.1109/ROBIO58561.2023.10354813

Gunjan Gupta, Vedansh Mittal, K. M. Krishna

{"title":"DynGraspVS: Servoing Aided Grasping for Dynamic Environments","authors":"Gunjan Gupta, Vedansh Mittal, K. M. Krishna","doi":"10.1109/ROBIO58561.2023.10354813","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354813","url":null,"abstract":"Visual servoing has been gaining popularity in various real-world vision-centric robotic applications. Autonomous robotic grasping often deals with unseen and unstructured environments, and in this task, Visual Servoing has been able to generate improved end-effector control by providing visual feedback. However, existing Servoing-aided grasping methods tend to fail at the task of grasping in dynamic environments i.e. - moving objects.In this paper, we introduce DynGraspVS, a novel Image-based Visual Servoing-aided Grasping approach that models the motion of moving objects in its interaction matrix. Leveraging a single-step rollout strategy, our approach achieves a remarkable increase in success rate, while converging faster and achieving a smoother trajectory, while maintaining precise alignments in six degrees of freedom. By integrating the velocity information into the interaction matrix, our method is able to successfully complete the challenging task of robotic grasping in the case of dynamic objects, while outperforming existing deep Model Predictive Control (MPC) based methods in the PyBullet simulation environment. We test it with a range of objects in the YCB dataset with varying range of shapes, sizes, and material properties. We report various evaluation metrics such as photometric error, success rate, time taken, and trajectory length.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"37 2","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187294","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}

引用次数: 0

A Flexible Towed Aerial Robot System for Stable X-ray Inspection of Power Lines 用于对电力线进行稳定 X 射线检查的柔性拖曳空中机器人系统

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2023-12-04 DOI: 10.1109/ROBIO58561.2023.10354790

Zhaoying Wang, Xu Li, Wenkang Hu

{"title":"A Flexible Towed Aerial Robot System for Stable X-ray Inspection of Power Lines","authors":"Zhaoying Wang, Xu Li, Wenkang Hu","doi":"10.1109/ROBIO58561.2023.10354790","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354790","url":null,"abstract":"Regular defect inspection of the power line using X-ray is essential for the maintenance of the power line. Usually, conducting such an inspection with a wheeled robot requires dragging the robot from the ground and carefully placing it upon the power line, which is laborious and unsafe. To improve inspection efficiency, the newly developed unmanned aerial vehicle (UAV) provides a promising alternative. However, the positioning error from Global Navigation Satellite System (GNSS) brings the small-scaled drifting movement of the UAV and X-ray camera system, which leads to imaging blur. To cope with this issue, we design a flexible towed aerial robot system to alleviate the instability of the X-ray camera system. Specifically, the UAV and X-ray camera carrier are flexibly connected by a cluster of ropes, reducing the physical impact from the small-scaled drifting movement of the UAV. The permitting position error tolerance between the UAV and the carrier is analyzed. In addition, a guide wheel frame is designed on the carrier to facilitate the carrier’s smooth rolling along the power line. Furthermore, aiming to adapt to the different types of power lines, we design a lightweight motor-driven system to adjust the camera angles and the imaging plate position. Multi-view cameras are also designed to assist the pilot to control the UAV carrying the X-ray camera system landing on the power line. To verify the performance of the developed aerial robot system, we conduct real-world experiments with double bundle conductors and four bundle conductors. The results show that the developed system can efficiently complete inspection. The X-ray camera could obtain a stable imaging condition under the small drifting movement of the flight.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"95 12","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186822","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}

引用次数: 0

Spring Loaded Inverted Pendulum Model Based Musculoskeletal Biped Robot Design and Sequential Jumping Experiment 基于弹簧加载倒立摆模型的肌肉骨骼双足机器人设计与连续跳跃实验

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2023-12-04 DOI: 10.1109/ROBIO58561.2023.10354962

Yiqi Li, Yelin Jiang, Koh Hosoda

引用次数: 0

A Model for Cognitively Valid Lifelong Learning 认知有效的终身学习模式

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2023-12-04 DOI: 10.1109/ROBIO58561.2023.10355028

Hanne Say, E. Oztop

{"title":"A Model for Cognitively Valid Lifelong Learning","authors":"Hanne Say, E. Oztop","doi":"10.1109/ROBIO58561.2023.10355028","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10355028","url":null,"abstract":"In continual learning, usually a sequence of tasks are given to a learning agent and the performance of the agent after learning is measured in terms of resistance to catastrophic forgetting, efficacy of knowledge transfer and overall performance on the individual tasks. On the other hand, in multi-task learning, the system is designed to simultaneously acquire knowledge in multiple tasks, often through offline batch learning. A more cognitively valid scenario for lifelong robot learning would be to have a robotic agent to autonomously decide which task to engage and disengage while leveraging many-to-many knowledge transfer ability among tasks during online learning. In this study, we propose a novel lifelong robot learning architecture to fulfill the aforementioned desiderata, and show its validity in an environment where a robot learns the effects of its actions in different task settings. To realize the proposed model, we adopt learning progress measure for task selection, and have the tasks learn by independent neural networks with special structure that allows access to the neural layers of the non-selected tasks. The experiments conducted with a simulated robot arm in an object interaction scenario show that the proposed architecture yields better knowledge transfer and facilitates faster learning compared to baselines of fixed sequence task learning and isolated task learners with no knowledge transfer.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"83 8","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186865","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}

引用次数: 0

Backstepping sliding mode stabilization controller for underactuated unmanned surface vehicle based on disturbance observer 基于扰动观测器的欠驱动无人水面飞行器反步进滑模稳定控制器

2023 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2023-12-04 DOI: 10.1109/ROBIO58561.2023.10354777

Zhenzhen Tan, Wangjie Zhou, Jie Chen, Yang Xian, Quan Zhang, Long Li, Tao Yue, Yingzhong Tian, Sicheng Yi

引用次数: 0