View/state planning for three-dimensional object reconstruction under uncertainty
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
http://link.springer.com/content/pdf/10.1007/s10514-015-9531-3.pdf
Reference36 articles.
1. Aleotti, J., Rizzini, D. L., & Caselli, S. (2014). Perception and grasping of object parts from active robot exploration. Journal of Intelligent and Robotic Systems, 76(3–4), 401–425.
2. Connolly, C. I. (1985). The determination of next best views. In Proceedings of the IEEE international conference on robotics and automation (Vol. 2, pp. 432–435). St. Louis, MO, USA.
3. Espinoza, J., Sarmiento, A., Murrieta-Cid, R., & Hutchinson, S. (2011). A motion planning strategy for finding an object with a mobile manipulator in 3-d environments. Advanced Robotics, 25(13–14), 1627–1650.
4. Foissotte, T., Stasse, O., Escande, A., Wieber, P.-B., & Kheddar, A. (2009). A two-steps next-best-view algorithm for autonomous 3d object modeling by a humanoid robot. In Proceedings of the IEEE international conference on robotics and automation (pp. 1078–1083). Kobe, Japan.
5. Hornung, A., Wurm, K. M., Bennewitz, M., Stachniss, C., & Burgard, W. (2013). Octomap: An efficient probabilistic 3d mapping framework based on octrees. Autonomous Robots, 34(3), 189–206.
Cited by 39 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. MVG-Net: LiDAR Point Cloud Semantic Segmentation Network Integrating Multi-View Images;Remote Sensing;2024-07-31
2. Next Best View Planning via Deep Reinforcement Leaning for 3D Reconstruction of Turbine Blades;2024 36th Chinese Control and Decision Conference (CCDC);2024-05-25
3. Sparse Sampling-Based View Planning for Complex Geometries;IEEE Sensors Journal;2024-05-01
4. Autonomous view planning methods for 3D scanning;Automation in Construction;2024-04
5. The surface edge explorer (SEE): A measurement-direct approach to next best view planning;The International Journal of Robotics Research;2024-02-15
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3