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陈铂垒 等: 面向具身人工智能的物体目标导航综述                                                        1751


                      free  learning.  In:  Proc.  of  the  2022  IEEE/CVF  Conf.  on  Computer  Vision  and  Pattern  Recognition.  New  Orleans:  IEEE,  2022.
                      18868–18878. [doi: 10.1109/CVPR52688.2022.01832]
                 [21]  Zhu MZ, Zhao BL, Kong T. Navigating to objects in unseen environments by distance prediction. In: Proc. of the 2022 IEEE/RSJ Int’l
                      Conf. on Intelligent Robots and Systems. Kyoto: IEEE, 2022. 10571–10578. [doi: 10.1109/IROS47612.2022.9981766]
                 [22]  Zhang JZ, Dai L, Meng FP, Fan QN, Chen XL, Xu K, Wang H. 3D-aware object goal navigation via simultaneous exploration and
                      identification. In: Proc. of the 2023 IEEE/CVF Conf. on Computer Vision and Pattern Recognition. Vancouver: IEEE, 2023. 6672–6682.
                      [doi: 10.1109/CVPR52729.2023.00645]
                 [23]  Min SY, Tsai YHH, Ding W, Farhadi A, Salakhutdinov R, Bisk Y, Zhang J. Object goal navigation with end-to-end self-supervision.
                      arXiv:2212.05923, 2022.
                 [24]  Yang W, Wang XL, Farhadi A, Gupta A, Mottaghi R. Visual semantic navigation using scene priors. In: Proc. of the 7th Int’l Conf. on
                      Learning Representations. New Orleans: ICLR, 2019.
                 [25]  Wani S, Patel S, Jain U, Chang AX, Savva M. MultiON: Benchmarking semantic map memory using multi-object navigation. In: Proc.
                      of the 34th Int’l Conf. on Neural Information Processing Systems. Vancouver: Curran Associates Inc., 2020. 813.
                 [26]  Raychaudhuri S, Campari T, Jain U, Savva M, Chang AX. Reduce, reuse, recycle: Modular multi-object navigation. arXiv:2304.03696,
                      2023.
                 [27]  Sadek A, Bono G, Chidlovskii B, Baskurt A, Wolf C. Multi-object navigation in real environments using hybrid policies. In: Proc. of the

                      2023  IEEE  Int’l  Conf.  on  Robotics  and  Automation  (ICRA).  London:  IEEE,  2023.  4085–4091.  [doi:  10.1109/ICRA48891.2023.
                      10161030]
                 [28]  Zeng HT, Song XH, Jiang SQ. Multi-object navigation using potential target position policy function. IEEE Trans. on Image Processing,
                      2023, 32: 2608–2619. [doi: 10.1109/TIP.2023.3263110]
                 [29]  Marza P, Matignon L, Simonin O, Wolf C. Multi-object navigation with dynamically learned neural implicit representations. In: Proc. of
                      the 2023 IEEE/CVF Int’l Conf. on Computer Vision. Paris: IEEE, 2023. 10970–10981. [doi: 10.1109/ICCV51070.2023.01010]
                 [30]  Chen PH, Ji DY, Lin KY, Hu WW, Huang WB, Li TH, Tan MK, Gan C. Learning active camera for multi-object navigation. In: Proc. of
                      the 36th Int’l Conf. on Neural Information Processing Systems. New Orleans: Curran Associates Inc., 2022. 2078.
                 [31]  Ye J, Batra D, Das A, Wijmans E. Auxiliary tasks and exploration enable objectgoal navigation. In: Proc. of the 2021 IEEE/CVF Int’l
                      Conf. on Computer Vision. Montreal: IEEE, 2021. 16097–16106. [doi: 10.1109/ICCV48922.2021.01581]
                 [32]  Zhang SX, Song XH, Bai YB, Li WJ, Chu YK, Jiang SQ. Hierarchical object-to-zone graph for object navigation. In: Proc. of the 2021
                      IEEE/CVF Int’l Conf. on Computer Vision. Montreal: IEEE, 2021. 15110–15120. [doi: 10.1109/ICCV48922.2021.01485]
                 [33]  Li  WJ,  Song  XH,  Bai  YB,  Zhang  SX,  Jiang  SQ.  ION:  Instance-level  object  navigation.  In:  Proc.  of  the  29th  ACM  Int’l  Conf.  on
                      Multimedia. ACM, 2021. 4343–4352. [doi: 10.1145/3474085.3475575]
                 [34]  Mayo B, Hazan T, Tal A. Visual navigation with spatial attention. In: Proc. of the 2021 IEEE/CVF Conf. on Computer Vision and
                      Pattern Recognition. Nashville: IEEE, 2021. 16893–16902. [doi: 10.1109/CVPR46437.2021.01662]
                 [35]  Li WY, Hong RX, Shen JW, Yuan L, Lu Y. Transformer memory for interactive visual navigation in cluttered environments. IEEE
                      Robotics and Automation Letters, 2023, 8(3): 1731–1738. [doi: 10.1109/LRA.2023.3241803]
                 [36]  Du HM, Yu X, Zheng L. Learning object relation graph and tentative policy for visual navigation. In: Proc. of the 16th European Conf.
                      on Computer Vision. Glasgow: Springer, 2020. 19–34. [doi: 10.1007/978-3-030-58571-6_2]
                 [37]  Du HM, Li LC, Huang Z, Yu X. Object-goal visual navigation via effective exploration of relations among historical navigation states.
                      In: Proc. of the 2023 IEEE/CVF Conf. on Computer Vision and Pattern Recognition. Vancouver: IEEE, 2023. 2563–2573. [doi: 10.1109/
                      CVPR52729.2023.00252]
                 [38]  Zhang SX, Song XH, Li WJ, Bai YB, Yu XY, Jiang SQ. Layout-based causal inference for object navigation. In: Proc. of the 2023
                      IEEE/CVF Conf. on Computer Vision and Pattern Recognition. Vancouver: IEEE, 2023. 10792–10802. [doi: 10.1109/CVPR52729.2023.
                      01039]
                 [39]  Wortsman M, Ehsani K, Rastegari M, Farhadi A, Mottaghi R. Learning to learn how to learn: Self-adaptive visual navigation using meta-
                      learning. In: Proc. of the 2019 IEEE/CVF Conf. on Computer Vision and Pattern Recognition. Long Beach: IEEE, 2019. 6743–6752.
                      [doi: 10.1109/CVPR.2019.00691]
                 [40]  Zhang SX, Li WJ, Song XH, Bai YB, Jiang SQ. Generative meta-adversarial network for unseen object navigation. In: Proc. of the 17th
                      European Conf. on Computer Vision. Tel Aviv: Springer, 2022. 301–320. [doi: 10.1007/978-3-031-19842-7_18]
                 [41]  Zhai A, Wang SL. PEANUT: Predicting and navigating to unseen targets. In: Proc. of the 2023 IEEE/CVF Int’l Conf. on Computer
                      Vision. Paris: IEEE, 2023. 10892–10901. [doi: 10.1109/ICCV51070.2023.01003]
                 [42]  Pal A, Qiu YD, Christensen H. Learning hierarchical relationships for object-goal navigation. In: Proc. of the 2020 Conf. on Robot
                      Learning. Cambridge: PMLR, 2021. 517–528.
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