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	Current-Aided Multiple-AUV Cooperative Localization and Target Tracking in Anchor-Free Environments 期刊论文 OAI收割 IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 3, 页码: 792-806 作者: Yichen Li; Wenbin Yu; Xinping Guan \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2023/03/02 Anchor-free belief propagation cooperative localization current-aided target tracking
	Location of Static Targets on the Seabed: A Study 期刊论文 OAI收割 JOURNAL OF INTERNET TECHNOLOGY, 2020, 卷号: 21, 期号: 5, 页码: 1563-1569 作者: Yao, Biyuan; Cao, Xinghui; Shen, Binjian; Li, Guiqing; Yin, Jianhua \| 收藏 \| 浏览/下载：27/0 \| 提交时间：2020/12/17 Static target Weighted centroid localization algorithm Least square localization algorithm Positioning error
	Multi-target localization and circumnavigation by a single agent using bearing measurements 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2015, 卷号: 25, 期号: 14, 页码: 2362-2374 作者: Deghat, Mohammad; Xia, Lu; Anderson, Brian D. O.; Hong, Yiguang \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2018/07/30 target localization circumnavigation persistence of excitation
	基于点云数据的表面检测与目标定位关键技术研究学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院大学, 2015 作者: 吴倩收藏 \| 浏览/下载：236/0 \| 提交时间：2015/09/02 点云数据表面检测路径规划光学导航目标定位 Point cloud Surface inspection Path planning Optical navigation Target localization
	网络化机器人系统下的目标跟踪与追捕研究学位论文 OAI收割工学硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2011 石坤收藏 \| 浏览/下载：20/0 \| 提交时间：2015/09/02 网络化机器人系统目标定位跟踪追捕混合无线传感器网络 network robot system target localization tracking pursuit hybrid wireless sensor network
	on collaborative tracking of a target group using binary proximity sensors 期刊论文 OAI收割 JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2010, 卷号: 70, 期号: 8, 页码: 825-838 Cao Donglei; Jin Beihong; Das Sajal K.; Cao Jiannong \| 收藏 \| 浏览/下载：12/0 \| 提交时间：2011/05/24 Wireless sensor network Target group tracking Multi-sensor collaboration Localization error analysis
	Integrated intensity, orientation code and spatial information for robust tracking (EI CONFERENCE) 会议论文 OAI收割 2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007, May 23, 2007 - May 25, 2007, Harbin, China 作者: Wang Y.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：27/0 \| 提交时间：2013/03/25 real-time tracking is an important topic in computer vision. Conventional single cue algorithms typically fail outside limited tracking conditions. Integration of multimodal visual cues with complementary failure modes allows tracking to continue despite losing individual cues. In this paper we combine intensity orientation codes and special information to form a new intensity-orientation codes-special (IOS) feature to represent the target. The intensity feature is not affected by the shape variance of object and has good stability. Orientation codes matching is robust for searching object in cluttered environments even in the cases of illumination fluctuations resulting from shadowing or highlighting etc The spatial locations of the pixels are used which allow us to take into account the spatial information which is lost in traditional histogram. Histograms of intensity orientation codes and spatial information are employed for represent the target Mean shift algorithm is a nonparametric density estimation method. The fast and optimal mode matching can be achieved by this method. In order to reduce the compute time we use the mean shift procedure to reach the target localization. Experiment results show that the new method can successfully cope with clutter partial occlusions illumination change and target variations such as scale and rotation. The computational complexity is very low. If the size of the target is 3628 pixels it only needs 12ms to complete the method. 2007 IEEE.
	Target localization based on multisensor fusion for mobile robots 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION, 2006, 卷号: 21, 期号: 3, 页码: 165-173 作者: Yang, G. -S.; Hou, Z. -G.; Tan, M.; Yan, H. 收藏 \| 浏览/下载：15/0 \| 提交时间：2015/11/07 multisensor fusion polynomial approximation target localization target recognition mobile robot