机构

• 沈阳自动化研究所 [6]
• 合肥物质科学研究院 [2]
• 长春光学精密机械与物... [1]
• 自动化研究所 [1]

采集方式

• OAI收割 [10]

内容类型

• 会议论文 [5]
• 期刊论文 [5]

发表日期

• 2021 [1]
• 2020 [3]
• 2019 [1]
• 2016 [2]
• 2014 [1]
• 2010 [1]
• 更多

学科主题

筛选

浏览/检索结果: 共10条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Review on light vision detection of surface obstacles for USV 会议论文  OAI收割 Nanchang, China, May 28-30, 2021 作者:  Zhang, Chao;  Liu, Jinqing;  Xiao JC(肖金超);  Xiong JF(熊俊峰)   |  收藏  |  浏览/下载：45/0  |  提交时间：2021/08/21 Unmanned surface vehicle  visible vision  obstacle detection  environment perception   Robust Negative Obstacle Detection in Off-Road Environments Using Multiple LiDARs 会议论文  OAI收割 2020-4-20 作者:  Zhong ZY(钟泽宇);  Wang ZL(王智灵);  Lin LL(林玲龙);  Liang HW(梁华为);  Xu FY(徐凤煜)   |  收藏  |  浏览/下载：24/0  |  提交时间：2021/12/08 obstacle detection  autonomous vehicle  point cloud  geometric feature extraction  muti-frame fusion   基于三维激光雷达的道路边界提取和障碍物检测算法 期刊论文  OAI收割 模式识别与人工智能, 2020, 卷号: 33 -   |  收藏  |  浏览/下载：48/0  |  提交时间：2020/10/26 Unmanned Vehicle  3D Lidar  Road Boundary  Obstacle Detection  Point Cloud Processing  无人驾驶汽车  三维激光雷达  道路边界  障碍物检测  点云处理   Application of Improved Rapidly-exploring Random Trees (RRT) algorithm for Obstacle Avoidance of Snake-like Manipulator 会议论文  OAI收割 Beijing, China, October 13-16, 2020 作者:  Wang Z(王轸);  Chang J(常健);  Li B(李斌);  Wang C(王聪);  Liu C(刘春)   |  收藏  |  浏览/下载：23/0  |  提交时间：2020/12/05 snake-like manipulator  improved Rapidly-exploring Random Trees (RRT) algorithm  obstacle avoidance  collision detection   A Multi-Heuristic A* Algorithm Based on Stagnation Detection for Path Planning of Manipulators in Cluttered Environments 期刊论文  OAI收割 IEEE ACCESS, 2019, 卷号: 7, 页码: 135870-135881 作者:     |  收藏  |  浏览/下载：37/0  |  提交时间：2020/03/30 Path planning  obstacle avoidance  search-based planner  stagnation detection  multi-heuristic A*   Binocular Stereo Vision Based Obstacle Detection Method for Manipulator 会议论文  OAI收割 International Conference on Electrical Engineering and Automation (ICEEA), Xiamen, China, December 18-19, 2016 作者:  Liu, Qiang;  Zhang XX(张晓雪);  Liu JG(刘金国);  Zhang T(张天);  Ni ZY(倪智宇)   |  收藏  |  浏览/下载：30/0  |  提交时间：2017/09/12 Binocular stereo vision  Obstacle detection  Manipulator   Mobile robot obstacle avoidance algorithms based on information fusion of vision and sonar 期刊论文  OAI收割 International Journal of Future Generation Communication and Networking, 2016, 卷号: 9, 期号: 8, 页码: 111-120 作者:  Gao HW(高宏伟);  Wei, Qiuyang;  Yu Y(于洋);  Liu JG(刘金国) 收藏  |  浏览/下载：24/0  |  提交时间：2016/09/17 Binocular stereo vision  stereo matching  V-disparity  obstacle detection  T-S fuzzy neural network   Obstacle classification and 3D measurement in unstructured environments based on ToF cameras 期刊论文  OAI收割 SENSORS, 2014, 卷号: 14, 期号: 6, 页码: 10753-10782 作者:  Yu HS(余洪山);  Zhu J(朱江);  Wang YN(王耀南);  Jia, Wenyan;  Sun, Mingui   |  收藏  |  浏览/下载：16/0  |  提交时间：2014/11/03 Mobile Robotic Navigation  Obstacle Detection And Classification  Time-of-flight Camera  Region Of Interest Detection  Unstructured Environment Perception   V-disparity Based UGV Obstacle Detection in Rough Outdoor Terrain 期刊论文  OAI收割 自动化学报, 2010, 卷号: 36, 期号: 5, 页码: 667-673 作者:  Cong Y(丛杨);  Peng JJ(彭军舰);  Sun J(孙静);  Zhu LL(朱琳琳);  Tan DL(谈大龙) 收藏  |  浏览/下载：25/0  |  提交时间：2012/05/29 Main ground disparity (MGD)  V-disparity image  obstacle detection  unmanned ground vehicle (UGV)  outdoor unstructured environment   Innovative EDL GNC scheme for precise and safe mars landing missions (EI CONFERENCE) 会议论文  OAI收割 60th International Astronautical Congress 2009, IAC 2009, October 12, 2009 - October 16, 2009, Daejeon, Korea, Republic of 作者:  Liu Y.;  Zhang L.;  Zhang L.;  Liu Y.;  Liu Y. 收藏  |  浏览/下载：44/0  |  提交时间：2013/03/25 Future mars missions plan to land the more massive spacecrafts on the higher altitude and hazardous region  the landers should have the capability of high-precision autonomous navigation guidance and control (GNC) and automatic obstacle detection and avoidance to explore the scientific but hazardous region. The traditional deep space network (DSN) based GNC mode used in the Mars entry  descent and landing (EDL) phase has no ability to meet this goal  so the novel EDL GNC scheme is required to achieve the precise and safe Mars landing. This paper proposes the innovative Mars EDL GNC system scheme and the emphases are focused on the EDL navigation guidance and control with high landing accuracy and autonomous obstacle detection and avoidance.