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This study explores the potential of off-the-shelf Vision-Language Models (VLMs) for high-level robot planning in the context of autonomous navigation.
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X. Liang, H. Wang, Y.-H. Liu, Z. Liu, B. You, Z. Jing, and W. Chen, “Purely Image-Based Pose Stabilization of Nonholonomic Mobile Robots With a Truly Uncalibrated Overhead Camera,” IEEE Transactions on Robotics , vol. 36, no. 3, pp. 724–742, Jun. 2020, conference Name: IEEE Transactions on Robotics
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D. S. W. Williams, D. D. Martini, M. Gadd, and P. Newman, “Mitigating distributional shift in semantic segmentation via uncertainty estimation from unlabeled data,” IEEE Transactions on Robotics , vol. 40, pp. 3146–3165, 2024
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L. Robinson, M. Gadd, P. Newman, and D. D. Martini, “Robot-relay: Building-wide, calibration-less visual servoing with learned sensor handover networks,” in International Symposium on Experimental Robotics . Springer, 2023, pp. 129–140
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L. Robinson, D. De Martini, M. Gadd, and P. Newman, “Visual servoing on wheels: Robust robot orientation estimation in remote viewpoint control,” in 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2023, pp. 6364–6370
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D. Shah, B. Osiński, b. ichter, and S. Levine, “Lm-nav: Robotic navigation with large pre-trained models of language, vision, and action,” in Proceedings of The 6th Conference on Robot Learning , ser. Proceedings of Machine Learning Research, K. Liu, D. Kulic, and J. Ichnowski, Eds., vol. 205. PMLR, 14–18 Dec 2023, pp. 492–504. [Online]. Available: https://proceedings.mlr.press/v205/shah23b.html
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Z. Wang and G. Tian, “Goal-oriented visual semantic navigation using semantic knowledge graph and transformer,” IEEE Transactions on Automation Science and Engineering , 2024
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