2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM)最新文献

Using vision and haptic sensing for human-humanoid joint actions 利用视觉和触觉感知实现人-人形关节动作

2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM) Pub Date : 2013-11-12 DOI: 10.1109/RAM.2013.6758552

Don Joven Agravante, A. Cherubini, A. Kheddar

引用次数: 8

Determination of temporal window size for classifying the mean value of fNIRS signals from motor imagery 运动图像中fNIRS信号均值分类的时间窗大小的确定

2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM) Pub Date : 2013-11-01 DOI: 10.1109/RAM.2013.6758590

Noman Naseer, K. Hong

引用次数: 11

Development of a human-like narrator robot system in EXPO EXPO仿人机器人解说员系统的研制

2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM) Pub Date : 2013-11-01 DOI: 10.1109/RAM.2013.6758551

H. Ahn, Dong-Wook Lee, B. MacDonald

引用次数: 4

Cognitive planning based on Genetic Algorithm in computer-assisted interventions 基于遗传算法的认知规划在计算机辅助干预中的应用

2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM) Pub Date : 2013-11-01 DOI: 10.1109/RAM.2013.6758582

Wan Cheng Lim, Hongliang Ren

引用次数: 1

An improved parameterized approach for real time optimal motion planning of AUV moving in dynamic environment 动态环境下水下航行器实时优化运动规划的改进参数化方法

2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM) Pub Date : 2013-11-01 DOI: 10.1109/RAM.2013.6758567

Wenhao Luo, Jun Peng, Junchang Wang

引用次数: 3

Optimal placement and sizing of distributed generation in distribution power system based on multi-objective harmony search algorithm 基于多目标协调搜索算法的配电系统中分布式发电机组的最优布局与优化选型

2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM) Pub Date : 2013-11-01 DOI: 10.1109/RAM.2013.6758578

Yuan Liu, Yun-hua Li, Ke-yan Liu, W. Sheng

引用次数: 9

Simulation tool for 3D shape sensors based on Fiber Bragg gratings and optimization of measurement points 基于光纤光栅的三维形状传感器仿真工具及测量点优化

2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM) Pub Date : 2013-11-01 DOI: 10.1109/RAM.2013.6758583

C. Ledermann, H. Pauer, O. Weede, H. Woern

{"title":"Simulation tool for 3D shape sensors based on Fiber Bragg gratings and optimization of measurement points","authors":"C. Ledermann, H. Pauer, O. Weede, H. Woern","doi":"10.1109/RAM.2013.6758583","DOIUrl":"https://doi.org/10.1109/RAM.2013.6758583","url":null,"abstract":"3D shape sensing using Fiber Bragg gratings has attracted the interest of several research groups in recent years, but so far no possibility has been presented to optimize the sensing system by simulation. Almost always, the gratings (the points of strain measurement) are distributed equidistantly, and the reconstruction algorithm has not been verified by simulation. In this paper we present our simulation tool that works on a mathematical basis and includes two parts: the first part describes how to determine the strains of Fiber Bragg gratings mounted along a given shape. The second part describes our algorithm to reconstruct the shape from this strain data using theory of differential geometry. This reconstruction algorithm is evaluated within the simulation environment and can be adapted to different system behaviors like circular bending of the instrument, cubic bending or bending according to the Euler beam theory. Furthermore, the gratings can be optimized with respect to their position and designated Bragg wavelength. To demonstrate the effectiveness of the simulation tool, an optimization has been conducted for the grating positions along a shape with two independent bendable segments. For each configuration of the shape, the reconstruction results using the optimized grating positions were significantly better than when using equidistantly distributed gratings.","PeriodicalId":287085,"journal":{"name":"2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131512409","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: 14

Properties of lateral-pendulum-controlled unicycle robot in states of balance and motion 横摆控制独轮车机器人在平衡和运动状态下的特性

2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM) Pub Date : 2013-11-01 DOI: 10.1109/RAM.2013.6758577

Y. Daud, A. Mamun, Jian-xin Xu

引用次数: 4

Non-contact parametric estimation and localization of human head for transcranial magnetic stimulation (TMS) 经颅磁刺激人体头部非接触参数估计与定位

2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM) Pub Date : 2013-11-01 DOI: 10.1109/RAM.2013.6758591

Yeshwin M. Srinivasa, S. Foong, D. Madhavan, U-Xuan Tan, Liang Hu, Xin Fu, Yew Long Lo

{"title":"Non-contact parametric estimation and localization of human head for transcranial magnetic stimulation (TMS)","authors":"Yeshwin M. Srinivasa, S. Foong, D. Madhavan, U-Xuan Tan, Liang Hu, Xin Fu, Yew Long Lo","doi":"10.1109/RAM.2013.6758591","DOIUrl":"https://doi.org/10.1109/RAM.2013.6758591","url":null,"abstract":"Transcranial magnetic stimulation (TMS) has been gaining popularity in various neurological treatments and an automated platform with better precision is desired. This paper proposes a dexterous articulated robotic arm with TMS coils as the end-effectors. Most robotic arm based positioning systems utilize vision feedback from stationary cameras for dynamic positioning, but these are not suitable for clinics with limited space. In this paper, a compact approach to identify the size, position and orientation of the patient's head relative to a robotic arm using a non-vision, range data based system is proposed. An accurate distance measurement sensor is used in tandem with a robotic arm to scan the patient's head and produce a growing 3D point cloud. An efficient surface fitting algorithm, taking into consideration the similarity of the human head to an ellipsoid, is presented to simultaneously extract position, orientation and geometrical information of the target head. Simulations and experiments are conducted and promising results are obtained to demonstrate its capability to identify the location and orientation of the patient's head.","PeriodicalId":287085,"journal":{"name":"2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132891033","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

Human velocity tracking and localization using 3 IMU sensors 使用3个IMU传感器的人体速度跟踪和定位

2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM) Pub Date : 2013-11-01 DOI: 10.1109/RAM.2013.6758554

Qilong Yuan, I. Chen, A. Causo

{"title":"Human velocity tracking and localization using 3 IMU sensors","authors":"Qilong Yuan, I. Chen, A. Causo","doi":"10.1109/RAM.2013.6758554","DOIUrl":"https://doi.org/10.1109/RAM.2013.6758554","url":null,"abstract":"In sports training and exercises, the velocity and position of the person is very important for motion evaluation. Despite of the development in motion capturing, a proper method for velocity monitoring for daily use is still not elaborated. In this work, a velocity tracking and localization method using only three IMU sensors is introduced. In the method, a reference root point on the pelvis is chosen to represent the velocity and location of the person. The three sensors are located at the right shank, right thigh and the pelvis to measure the kinematics of the lower limbs. Through proper acceleration error canceling algorithm, the acceleration data is refined to fuse with the root velocity calculated from lower limb kinematics. The drift-free and accurate 3D velocity result is achieved in this manner. The location of the person is tracked based on this velocity result and the limb kinematic subsequently. The benchmark study with the commercial optical reference shows that the accuracy in velocity tracking is within 3% of the moving velocity and localization accuracy is within 2% in both normal walking and jumping. For the utilize conveniences of the small-size wearable IMU sensors, this proposed velocity tracking and localization method is very useful in everyday applications both indoor and outdoor.","PeriodicalId":287085,"journal":{"name":"2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121175787","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: 8