Acknowledgement
This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2022-0-00907, Development of AI Bots Collaboration Platform and Self-organizing AI, 80% and No.RS-2020-II201373, Artificial Intelligence Graduate School Program (Hanyang University), 20%).
References
- M. D. Graaf, S. B. Allouch, and J. V. Diik, "Why do they refuse to use my robot?: Reasons for non-use derived from a long-term home study," 2017 ACM/IEEE International Conference on Human-Robot Interaction, Vienna, Austria, pp. 224-233, 2017, DOI: 10.1145/2909824.3020236.
- H. Guo, F. Wu, Y. Qin, R. Li, K. Li, and K. Li, "Recent Trends in Task and Motion Planning for Robotics: A Survey," ACM Comput. Surv, vol. 55, no. 13, pp. 1-36, Jul., 2023, DOI: 10.1145/3583136.
- M. Ghallab, C. A. Knoblock, D. E. Wilkins, A. Barrett, D. Christianson, M. T. Friedman, C. Kwok, K. Golden, S. Penberthy, D. E. Smith, Y. Sun, and D. Weld, "PDDL - The Planning Domain Definition Language," Technical report, Yale Center for Computational Vision and Control, 1998, [Online], https://www.researchgate.net/publication/2278933.
- C. Paxton, Y. Barnoy, K. Katyal, R. Arora, and G. D. Hager, "Visual robot task planning," 2019 International conference on robotics and automation (ICRA), pp. 8832-8838, 2019, DOI: 10.1109/ICRA.2019.8793736.
- T. Silver, V. Hariprasad, R. S. Shuttleworth, N. Kumar, T. Lozano-Perez, and L. P. Kaelbling, "PDDL planning with pretrained large language models," NeurIPS 2022 foundation models for decision making workshop, 2022, [Online], https://openreview.net/forum?id=1QMMUB4zfl, Accessed: Apr. 23, 2024.
- J. Zhou, G. Cui, S. Hu, Z. Zhang, C. Yang, Z. Liu, L. Wang, C. Li, and M. Sun, "Graph neural networks: A review of methods and applications," AI open, vol. 1, pp.57-81, 2020, DOI: 10.1016/j.aiopen.2021.01.001.
- T. Silver, R. Chitnis, A. Curtis, J. Tenenbaum, T. Lozano-Perez, and L. P. Kaelbling, "Planning with learned object importance in large problem instances using graph neural networks," Proceedings of the AAAI conference on artificial intelligence, pp. 11962-11971, Sept., 2021, DOI: 10.48550/arXiv.2009.05613.
- K. He, X. Zhang, S. Ren, and J. Sun, "Deep residual learning for image recognition," Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 770-778, 2016, DOI: 10.48550/arXiv.1512.03385.
- J. J. Kuffner and S. M. LaValle, "RRT-connect: An efficient approach to single-query path planning," Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No. 00CH37065), San Francisco, CA, USA, pp. 995-1001, 2000, vol. 2, DOI: 10.1109/ROBOT.2000.844730.