2016 IEEE International Conference on Real-time Computing and Robotics (RCAR)最新文献_第9页

Environment feature recognition algorithm for rescue robot based on a 2D laser radar 基于二维激光雷达的救援机器人环境特征识别算法

2016 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2016-06-01 DOI: 10.1109/RCAR.2016.7784054

Xizhe Zang, Can Zhang, Yixiang Liu, Jie Zhao

引用次数: 1

Bidding strategy in continuous double auction market based on Fuzzy Cognitive Map 基于模糊认知图的连续双拍市场竞价策略

2016 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2016-06-01 DOI: 10.1109/RCAR.2016.7784016

H. Luan, Hongbin Dong, Qi Feng, Yue Pan

引用次数: 3

The method of linear inflation control in Ambulatory Blood Pressure measurement at finger 手指动态血压测量中的线性膨胀控制方法

2016 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2016-06-01 DOI: 10.1109/RCAR.2016.7783993

Pandeng Zhang, Jie Zhang, Quanli Qiu, Ye Chen, Jia Liu

引用次数: 0

Design and analysis of a two-DOF coupling motion robotic joint 二自由度耦合运动机器人关节的设计与分析

2016 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2016-06-01 DOI: 10.1109/RCAR.2016.7784093

He Huang, Erbao Dong, Linlei Zhou, Zhuo Duan, Chunshan Liu, Jin Luo, Min Xu, Jie Yang

{"title":"Design and analysis of a two-DOF coupling motion robotic joint","authors":"He Huang, Erbao Dong, Linlei Zhou, Zhuo Duan, Chunshan Liu, Jin Luo, Min Xu, Jie Yang","doi":"10.1109/RCAR.2016.7784093","DOIUrl":"https://doi.org/10.1109/RCAR.2016.7784093","url":null,"abstract":"In this paper, a robotic joint with a two-DOF coupling motion is proposed for higher payload ability, power density and speed. With these advantages the joint is ideal for use in robots, especially multi-DOF manipulators. The entire robot manipulator composed of these joints is not involved in this paper. It will be reported in detail in a future publication. Here we just focus on the robotic joint. This robotic joint which is configured as a series-parallel hybrid structure can be called as angular swivel joint. And the joint can move on a spherical surface whose apex angle is 100° by the coupling motions of two independent motor-reducer drive systems. Details of the mechanism design, kinematics analysis and differential kinematics will be depicted. In addition, all motions of the joint can be divided into two modes: mode 1 is that the two motor-reducer systems work in the same speed and with the opposite direction (SSOD); and mode 2 is that the two motor-reducer drive systems work in the same speed and with the same direction (SSSD). Moreover, a unique control strategy based on these two basic motion modes are presented. Finally, simulations and experiments are implemented to verify the feasibility and performance of the joint.","PeriodicalId":402174,"journal":{"name":"2016 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128645329","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

Pose measurement of a non-cooperative spacecraft based on circular features 基于圆形特征的非合作航天器位姿测量

2016 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2016-06-01 DOI: 10.1109/RCAR.2016.7784029

Yang Liu, Zongwu Xie, Bin Wang, Hong Liu

引用次数: 6

A novel calibration method for the photometric stereo system with non-isotropic LED lamps 一种新的非各向同性LED灯光度立体系统标定方法

2016 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2016-06-01 DOI: 10.1109/RCAR.2016.7784041

Y. Nie, Zhan Song, Ming Ji, Lei Zhu

引用次数: 7

Soft damper for quick stabilization of soft robotic actuator 用于柔性机器人执行器快速稳定的软阻尼器

2016 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2016-06-01 DOI: 10.1109/RCAR.2016.7784074

Feng Ni, A. Henning, K. Tang, L. Cai

引用次数: 9

Real-time tag recognition based on morphology and local contrast 基于形态学和局部对比的实时标签识别

2016 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2016-06-01 DOI: 10.1109/RCAR.2016.7784100

Zhiqin Chen, Yufeng Zhang, Hesheng Wang, Weidong Chen

{"title":"Real-time tag recognition based on morphology and local contrast","authors":"Zhiqin Chen, Yufeng Zhang, Hesheng Wang, Weidong Chen","doi":"10.1109/RCAR.2016.7784100","DOIUrl":"https://doi.org/10.1109/RCAR.2016.7784100","url":null,"abstract":"With the development of computer and robotic technology, more and more miscellaneous work has been done by robots rather than men. In this case, robot vision, especially object recognition, which can help to locate objects in captured images and extract valuable information from those objects, becomes a significant part in robot design and realization. This process is expected to be real-time. In this paper, the aim is to find out the real-time and accurate algorithms to localize and recognize particular tags. Firstly, new special tags are designed. Then two tag corner localization methods are proposed, in which one is based on morphology and another is based on local contrast. And the character recognition based on OCR are also described. In the end, based on Library Management Robot (LMR), some experiments are taken. As a result, the two tag localization algorithms turn out to have complementary features in recognition distance. Meanwhile, comparing to other methods, the new methods can quickly and accurately extract tags and their information under various conditions including unexpected shadows, different light conditions and different backgrounds.","PeriodicalId":402174,"journal":{"name":"2016 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117203063","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: 2

Robotic manipulation planning using dynamic RRT 基于动态RRT的机器人操作规划

2016 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2016-06-01 DOI: 10.1109/RCAR.2016.7784080

Hao Deng, Zeyang Xia, Jing Xiong

{"title":"Robotic manipulation planning using dynamic RRT","authors":"Hao Deng, Zeyang Xia, Jing Xiong","doi":"10.1109/RCAR.2016.7784080","DOIUrl":"https://doi.org/10.1109/RCAR.2016.7784080","url":null,"abstract":"When a robot manipulator performs tasks in a dynamic unstructured environment, it not only should account for where and how it should move, but also ensure that the robot can effectively avoid collisions with static and moving obstacles. Planning in absolutely unstructured and dynamic environment is much more challenging, up-to-date there is no universal solution to this problem. In this paper, we believed the concept that for motion planning in real dynamic environments, usually there is only a part of a path invalidated by obstacles, and only this part needs replanning. Thus, in this paper a practical strategy was presented for motion planning in dynamic environments. First, a variant dynamic Rapidly-exploring Random Tree (RRT) planner was designed to combine global planning with local replanning. Then, the proposed dynamic RRT algorithm was implemented under Robotic Operation System (ROS) framework and applied to a 7-degree-of-freedom manipulator. Experimental results have shown that the proposed dynamic RRT planner can plan and execute movement of robot manipulator between a starting and target position while preserving task constraints and reacting to environment changes in real time.","PeriodicalId":402174,"journal":{"name":"2016 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127747741","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: 5

A new algorithm for obstacle segmentation in dynamic environments using a RGB-D sensor 基于RGB-D传感器的动态环境中障碍物分割新算法

2016 IEEE International Conference on Real-time Computing and Robotics (RCAR) Pub Date : 2016-06-01 DOI: 10.1109/RCAR.2016.7784057

Gaoqiang Yang, Fucai Chen, Wen Chen, Mu Fang, Yunhui Liu, Luyang Li

{"title":"A new algorithm for obstacle segmentation in dynamic environments using a RGB-D sensor","authors":"Gaoqiang Yang, Fucai Chen, Wen Chen, Mu Fang, Yunhui Liu, Luyang Li","doi":"10.1109/RCAR.2016.7784057","DOIUrl":"https://doi.org/10.1109/RCAR.2016.7784057","url":null,"abstract":"Obstacle detection is one of the main components of the control system and navigation of autonomous vehicles. This paper presents a novel approach to obstacle detection and segmentation with a RGB-D sensor. Different from the traditional approaches which only detect whether there exist obstacles, our approach not only can detect the obstacles but also can distinguish between dynamic obstacles and static obstacles. Base on the information received by the kinect sensor, the mobile robot can choose different avoidance strategy when facing different kinds of obstacles intelligently. First, we get a 3D point cloud from the depth image and compute the height of each point from ground plane which is estimated during a calibration step. In this step, we can discriminate which point belongs to obstacles. Then we use a batch of depth images to get the dynamic objects of each image. Finally, the obstacle map is an orthographic projection of these obstacle points along the normal to the ground plane. Experimental results carried out with a mobile platform in an indoor environment have shown that the system can detect and segment stationary and moving obstacles.","PeriodicalId":402174,"journal":{"name":"2016 IEEE International Conference on Real-time Computing and Robotics (RCAR)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133470003","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: 2