Blog(2)

• A Soft Introduction to Visual SLAM

  It is no longer a secret that everyone meets robots in everyday life. Robots could be found everywhere: from children’s toys and to autonomous vehicles. Robots help us to live by coping with everyday routine tasks, entertaining us, and giving us new abilities. Some of the most useful service robots are human assistant robots performing distant, repetitive and tedious jobs. Wide variety of examples include package delivery robots, robot-waiters in restaurants,

• DH-LC: Hierarchical Matching and Hybrid Bundle Adjustment Towards Accurate and Robust Loop Closure

  Visual simultaneous localization and mapping (SLAM) inevitably produces the accumulated drift in mapping and localization due to camera calibration errors, feature matching errors, etc. It is challenging to achieve drift-free localization and obtain an accurate global map.

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Publications(5)

• DH-LC: Hierarchical Matching and Hybrid Bundle Adjustment Towards Accurate and Robust Loop Closure

  AuthorXiongfeng Peng, zhihua Liu, Qiang Wang, Yun-Tae Kim, Hong-Seok Lee

  PublishedIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

  Date2022-12-26

• A Comparison of Modern General-Purpose Visual SLAM Approaches

  AuthorAlexey Merzlyakov, Steve Macenski

  PublishedIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

  Date2021-09-30

• Accurate Visual-Inertial SLAM by Feature Re-identification

  AuthorXiongfeng Peng, Zhihua Liu, Qiang Wang, Yun-Tae Kim, Myungjae Jeon

  PublishedIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

  Date2021-09-27

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News(4)

• Samsung R&D Institute China – Beijing Secures First Place in ICCV 2023 SLAM Challenge

  Simultaneous Localization and Mapping (SLAM) is extensively used in Extended Reality(XR) Head Mounted Display(HMD), robots, autonomous driving, and various other fields.

• Samsung R&D Institute China – Beijing Secures First Place in ICCV 2023 SLAM Challenge

  Simultaneous Localization and Mapping (SLAM) is extensively used in Extended Reality(XR) Head Mounted Display(HMD), robots, autonomous driving, and various other fields.

• [Blog] DH-LC: Hierarchical Matching and Hybrid Bundle Adjustment Towards Accurate and Robust Loop Closure

  Visual simultaneous localization and mapping (SLAM) inevitably produces the accumulated drift in mapping and localization due to camera calibration errors, feature matching errors, etc. It is challenging to achieve drift-free localization and obtain an accurate global map.

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