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iSeries

This repo collects the source code and projects related to Imperative Learning.

Imperative learning (IL) was first formally defined in this long article:

Its source code is (or will be) available in the following repositories.

  • iSLAM: Imperative SLAM.

    Taimeng Fu, Shaoshu Su, Yiren Lu, Chen Wang.

    IEEE Robotics and Automation Letters (RA-L), 2024.

    Code link: https://github.com/sair-lab/iSLAM

  • iPlanner: Imperative Path Planning.

    Fan Yang, Chen Wang, Cesar Cadena, Marco Hutter.

    Robotics: Science and Systems (RSS), 2023.

    Code link: https://github.com/sair-lab/iPlanner

  • iMTSP: Solving Min-Max Multiple Traveling Salesman Problem with Imperative Learning.

    Yifan Guo, Zhongqiang Ren, Chen Wang.

    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024.

    Code link: https://github.com/sair-lab/iMTSP

  • iMatching: Imperative Correspondence Learning.

    Zitong Zhan, Dasong Gao, Yun-Jou Lin, Youjie Xia, Chen Wang.

    European Conference on Computer Vision (ECCV), 2024.

    Code link: https://github.com/sair-lab/iMatching

  • iA*: Imperative Learning-based A* Search for Pathfinding.

    Xiangyu Chen, Fan Yang, Chen Wang.

    IEEE Robotics and Automation Letters (RA-L), vol. 10, no. 12, pp. 12987–12994, 2025.

    Code link: https://github.com/sair-lab/iAstar

  • iWalker: Imperative Visual Planning for Walking Humanoid Robot.

    Xiao Lin, Yuhao Huang, Taimeng Fu, Xiaobin Xiong, Chen Wang.

    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2865–2872, 2025.

  • iKap: Kinematics-aware Planning with Imperative Learning.

    Qihang Li, Zhuoqun Chen, Haoze Zheng, Haonan He, Shaoshu Su, Junyi Geng, Chen Wang.

    IEEE International Conference on Robotics and Automation (ICRA), pp. 10164–10170, 2025.

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