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pro vyhledávání: '"Hart, Justin"'
HRI research using autonomous robots in real-world settings can produce results with the highest ecological validity of any study modality, but many difficulties limit such studies' feasibility and effectiveness. We propose Vid2Real HRI, a research f
Externí odkaz:
http://arxiv.org/abs/2403.15798
Autor:
Hauser, Elliott, Chan, Yao-Cheng, Bhalani, Ruchi, Kuchimanchi, Alekhya, Siddiqui, Hanaa, Hart, Justin
A single mobile service robot may generate hundreds of encounters with pedestrians, yet there is little published data on the factors influencing these incidental human-robot encounters. We report the results of a between-subjects experiment (n=222)
Externí odkaz:
http://arxiv.org/abs/2311.04454
Autor:
Stark, Carson, Chun, Bohkyung, Charleston, Casey, Ravi, Varsha, Pabon, Luis, Sunkari, Surya, Mohan, Tarun, Stone, Peter, Hart, Justin
This work introduces a robotics platform which embeds a conversational AI agent in an embodied system for natural language understanding and intelligent decision-making for service tasks; integrating task planning and human-like conversation. The age
Externí odkaz:
http://arxiv.org/abs/2310.06303
Semantic Segmentation combines two sub-tasks: the identification of pixel-level image masks and the application of semantic labels to those masks. Recently, so-called Foundation Models have been introduced; general models trained on very large datase
Externí odkaz:
http://arxiv.org/abs/2310.00783
Autor:
Latapie, Hugo, Yu, Shan, Hammer, Patrick, Thorisson, Kristinn R., Petrosyan, Vahagn, Kynoch, Brandon, Khare, Alind, Behnam, Payman, Tumanov, Alexey, Saxena, Aksheit, Aralikatti, Anish, Chen, Hanning, Imani, Mohsen, Archbold, Mike, Li, Tangrui, Wang, Pei, Hart, Justin
Traditional computer vision models often necessitate extensive data acquisition, annotation, and validation. These models frequently struggle in real-world applications, resulting in high false positive and negative rates, and exhibit poor adaptabili
Externí odkaz:
http://arxiv.org/abs/2307.10577
Autor:
Francis, Anthony, Pérez-D'Arpino, Claudia, Li, Chengshu, Xia, Fei, Alahi, Alexandre, Alami, Rachid, Bera, Aniket, Biswas, Abhijat, Biswas, Joydeep, Chandra, Rohan, Chiang, Hao-Tien Lewis, Everett, Michael, Ha, Sehoon, Hart, Justin, How, Jonathan P., Karnan, Haresh, Lee, Tsang-Wei Edward, Manso, Luis J., Mirksy, Reuth, Pirk, Sören, Singamaneni, Phani Teja, Stone, Peter, Taylor, Ada V., Trautman, Peter, Tsoi, Nathan, Vázquez, Marynel, Xiao, Xuesu, Xu, Peng, Yokoyama, Naoki, Toshev, Alexander, Martín-Martín, Roberto
A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation has advanced tremendously in recent years, the fair evaluation of algori
Externí odkaz:
http://arxiv.org/abs/2306.16740
Autor:
Han, Zhao, Senft, Emmanuel, Ahmad, Muneeb I., Bagchi, Shelly, Yazdani, Amir, Wilson, Jason R., Kim, Boyoung, Wen, Ruchen, Hart, Justin W., García, Daniel Hernández, Leonetti, Matteo, Mead, Ross, Mirsky, Reuth, Prabhakar, Ahalya, Zimmerman, Megan L.
The Artificial Intelligence (AI) for Human-Robot Interaction (HRI) Symposium has been a successful venue of discussion and collaboration on AI theory and methods aimed at HRI since 2014. This year, after a review of the achievements of the AI-HRI com
Externí odkaz:
http://arxiv.org/abs/2209.14292
Autor:
Balaban, David, Hart, Justin
Semantic mapping is the task of providing a robot with a map of its environment beyond the open, navigable space of traditional Simultaneous Localization and Mapping (SLAM) algorithms by attaching semantics to locations. The system presented in this
Externí odkaz:
http://arxiv.org/abs/2209.11432