2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)最新文献_第4页

Intuitive Control of Virtual Robots using Transformed Objects as Multiple Viewports 使用转换对象作为多视口的虚拟机器人的直观控制

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2019-12-01 DOI: 10.1109/ROBIO49542.2019.8961743

Rajeevlochana G. Chittawadigi, T. Matsumaru, S. Saha

引用次数: 1

Path Planning of Redundant Series Manipulators Based on Improved RRT Algorithms 基于改进RRT算法的冗余系列机械手路径规划

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2019-12-01 DOI: 10.1109/ROBIO49542.2019.8961770

Zhaoxing Chen, Yang Yang, Xiangrong Xu, A. Rodic

引用次数: 4

A Soft, Distributed, Digital 3-axis Skin Sensor Employing a Hybrid Permanent-Adjustable Magnetic Field 一种采用混合永久可调磁场的软分布数字三轴皮肤传感器

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2019-12-01 DOI: 10.1109/ROBIO49542.2019.8961708

A. C. Holgado, Javier Alejandro Alvarez Lopez, Tito Pradhono Tomo, S. Somlor, S. Sugano

引用次数: 1

A Novel Grasping Control Method for Dexterous Prosthesis based on Eye-tracking* 一种基于眼动追踪的灵巧假体抓取控制新方法

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2019-12-01 DOI: 10.1109/ROBIO49542.2019.8961380

Jie Li, Chunyuan Shi, Dapeng Yang, Hong Liu

{"title":"A Novel Grasping Control Method for Dexterous Prosthesis based on Eye-tracking*","authors":"Jie Li, Chunyuan Shi, Dapeng Yang, Hong Liu","doi":"10.1109/ROBIO49542.2019.8961380","DOIUrl":"https://doi.org/10.1109/ROBIO49542.2019.8961380","url":null,"abstract":"The state-of-art dexterous prosthetic hand with multi-degree-of-freedom urgently requires a control method to match its dexterity. The purpose of this paper is to develop a method on rapid grasp control of prosthetic hand based on eye-tracking and verify its effectiveness by experiments. Firstly, an interactive experiment platform was established. Based on the platform, the operator can select the necessary grasping pattern from a graphic interface through eye movement and trigger the selected pattern by gazing the target for a short time (~300ms). The selected grasp pattern will be fed back to the operator during the hand prosthesis performing reach-and-grasp tasks. Finally, to verify the effectiveness of this method, experiments were conducted by an able-bodied participant wearing the prosthesis to grasp some daily-used objects. Our result shows that, by adopting the eye tracking technology in the human visual channel, the grasp control of the prosthesis can be supervised and regulated in real-time and thus an effective interaction between the dexterous prosthesis and the operator can be achieved.","PeriodicalId":121822,"journal":{"name":"2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126520073","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: 6

An Approach to Fast Multi-Robot Exploration in Buildings with Inaccessible Spaces 具有不可接近空间的建筑物中多机器人快速探索方法

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2019-12-01 DOI: 10.1109/ROBIO49542.2019.8961681

Matthew McNeill, D. Lyons

{"title":"An Approach to Fast Multi-Robot Exploration in Buildings with Inaccessible Spaces","authors":"Matthew McNeill, D. Lyons","doi":"10.1109/ROBIO49542.2019.8961681","DOIUrl":"https://doi.org/10.1109/ROBIO49542.2019.8961681","url":null,"abstract":"The rapid exploration of unknown environments is a common application of autonomous multi-robot teams. For some types of exploration missions, a mission designer may possess some rudimentary knowledge about the area to be explored. For example, the dimensions of a building may be known, but not its floor layout or the location of furniture and equipment inside. For this type of mission, the Space-Based Potential Field (SBPF) method is an approach to multi-robot exploration which leverages a priori knowledge of area bounds to determine robot motion. Explored areas and obstacles exert a repulsive force, and unexplored areas exert an attractive force. While SBPF has advantages over other methods of robot exploration in terms of simplicity and performance, inaccessible space poses a problem: it exerts a permanent attractive force, pulling robots away from useful exploration elsewhere and creating minima at its boundary. Prior research established a simple method of filling in inaccessible space as a solid obstacle once an enclosing boundary is discovered; however, this method requires the entire enclosing boundary to be discovered before it can be filled. In this paper, we propose a novel combined SBPF and frontier-based method of robot exploration called O-SBPF. Our method adds two new space classifications: open, areas known to be accessible; and occluded, areas which may be inaccessible. We describe a ray-casting approach to designate areas as open or occluded, and incorporate this designation into potential vector calculations. We then show the effectiveness of O-SBPF using ROS/Stage in worlds with inaccessible space. O-SBPF significantly outperforms SBPF in rooms with large obstacles, successfully reaching 95% coverage while SBPF becomes stuck in a minima. In less complex rooms, we show that O-SBPF generally reaches 95% coverage at the same time or before SBPF.","PeriodicalId":121822,"journal":{"name":"2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"99 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128005739","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: 1

Highly Reflective Surface Measurement Based On Dual Stereo Monocular Structured Light System Fusion∗ 基于双立体单目结构光系统融合的高反射表面测量*

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2019-12-01 DOI: 10.1109/ROBIO49542.2019.8961876

Daochuan Wang, Kejing He, Congying Sui, C. Lyu, Yinping Lai, Huiwen Guo, Yunhui Liu

引用次数: 4

Motion Control of a Walking Support Robot Based on Gait Analysis 基于步态分析的行走支撑机器人运动控制

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2019-12-01 DOI: 10.1109/ROBIO49542.2019.8961488

Naoya Matsumoto, Shunta Togo, H. Yokoi, Yinlai Jiang

引用次数: 2

A Monocular Visual Odometry Combining Edge Enhance with Deep Learning 边缘增强与深度学习相结合的单目视觉里程计

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2019-12-01 DOI: 10.1109/ROBIO49542.2019.8961425

M. Yan, Chao-xia Shi, Yanqing Wang

引用次数: 3

Object Recall from Natural-Language Descriptions for Autonomous Robotic Grasping 基于自然语言描述的自主机器人抓取对象召回

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2019-12-01 DOI: 10.1109/ROBIO49542.2019.8961482

Achyutha Bharath Rao, Hui Li, Hongsheng He

{"title":"Object Recall from Natural-Language Descriptions for Autonomous Robotic Grasping","authors":"Achyutha Bharath Rao, Hui Li, Hongsheng He","doi":"10.1109/ROBIO49542.2019.8961482","DOIUrl":"https://doi.org/10.1109/ROBIO49542.2019.8961482","url":null,"abstract":"Humans acquire grasping skills through repeated interaction with the objects; and they internalize the knowledge of various physical attributes of such objects. Even blindfolded, humans can reasonably estimate a suitable grasp pose given only the object’s description. Human brain relies on the knowledge of having seen such objects and recalling its physical features such as shape, size, weight to estimate feasible grasps. In such a scenario, knowledge of an object’s features is key to executing a successful grasp. This paper aims to provide this ’recall’ ability to robots by proposing a methodology to represent human memory of objects with a dataset of objects and their physical features. A joint probability distance metric is derived, which can match the natural language descriptions to reference object features so as to recall and identify a particular object from the reference dataset, thereby facilitating better grasp planning. Experiments were performed to evaluate the accuracy of object recall, and simulation of an anthropomorphic robot hand was conducted for object grasping based on the recalled object features. The experiment results showed the accuracy of the proposed metric and effectiveness in object grasping.","PeriodicalId":121822,"journal":{"name":"2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134219239","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: 4

Prediction of Liver Respiratory Motion Based on Machine Learning 基于机器学习的肝脏呼吸运动预测

2019 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2019-12-01 DOI: 10.1109/ROBIO49542.2019.8961688

Xuezhi Bao, Deqiang Xiao, Baochun He, Wenchao Gao, Junliang Wang, F. Jia

{"title":"Prediction of Liver Respiratory Motion Based on Machine Learning","authors":"Xuezhi Bao, Deqiang Xiao, Baochun He, Wenchao Gao, Junliang Wang, F. Jia","doi":"10.1109/ROBIO49542.2019.8961688","DOIUrl":"https://doi.org/10.1109/ROBIO49542.2019.8961688","url":null,"abstract":"Hepatic respiratory movement has always been an important factor that affects the accuracy of liver interventional therapy. To improve the prediction accuracy of image-guided therapy, we proposed a liver breath prediction model that combines machine learning, surface point set sparse registration, and internal and external breath amplitude correlation. We used surface sparse point set registration to calculate the displacement vector field of the liver surface and the displacement vector field of a specified region of the abdominal surface. Using correlation analysis of the internal and external respiratory amplitudes, we selected the liver displacement vector field that is closest to the input respiratory signal as the optimal training data. A patient-specific model that combines local vector field optimization with abdominal surface similarity optimization was constructed by combining the liver surface and the abdominal surface after segmentation, and accurate motion prediction was realized based on principal component analysis (PCA). In an experiment on 7 patients, we adopted two experimental verification methods: (1) only one data collection stage and one cross-validation stage were used, and (2) the experimental data that were collected in the first stage were used as the training data set, and the experimental data that were collected in the second stage were used as the test data set. The prediction errors of the two methods were 0.35 ± 0.08 mm and 0.96 ± 0.40 mm, respectively. In this experiment, we combined surface sparse point set registration with an internal and external breath amplitude correlation method, which substantially improved the runtime and accuracy of the experiment compared with the traditional PCA method.","PeriodicalId":121822,"journal":{"name":"2019 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131624381","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: 1