The paper introduces a language‑guided approach for robots to join human groups by predicting socially compliant joining poses. It uses recursive spectral partitioning to generate candidate group subsets, ranks them with a language‑conditioned image–geometry model, and then applies a goal predictor that incorporates human‑formation priors to produce a multimodal energy–orientation map of feasible robot poses. Experiments on various group scenarios show competitive grounding accuracy, superior joining‑pose prediction, and successful real‑robot demonstrations in both static and dynamic settings.
By Zilin Fang, Zishuo Wang, Gim Hee Lee, David Hsu
arXiv:2609.40245v2 Announce Type: cross
Abstract: Robot navigation in dynamic, human-centered environments requires socially-compliant decisions grounded in robust scene understanding. Recent Vision-...
By Nathan Tsoi, Michael J. Munje, Tejas Oberoi, Rishab Maheshwari, Pengen Zheng, Tanush Chauhan, Peter Stone, Joydeep Biswas
arXiv:2607. 10991v1 Announce Type: cross Abstract: As mobile robots become more integrated into everyday human environments, social robot navigation is becoming essential for ensuring human comfort, safety, and trust.
By Ali Ahmadi, Hamed Rahimi, Adrien Jacquet Cretides, Marie Samson, Mahdi Khoramshahi, Mohamed Chetouani
arXiv:2607. 07021v1 Announce Type: new Abstract: Humans continuously coordinate with others in dynamic interactions, often through implicit, hard-to-quantify social norms that act as shared tacit expectations among interacting agents.
By Yi Yang, Siyuan Liu, Xin Gao, Huamu Sun, Chao Liu, Qing Zhou, Bingbing Nie
arXiv:2503. 14229v4 Announce Type: replace Abstract: Vision-and-Language Navigation (VLN) has been studied mainly in either discrete or continuous spaces, with little attention to dynamic, crowded environments.
By Yifei Dong, Fengyi Wu, Qi He, Lingdong Kong, Heng Li, Minghan Li, Zebang Cheng, Yuxuan Zhou, Jingdong Sun, Qi Dai, Alexander G Hauptmann, Zhi-Qi Cheng
arXiv:2609.23997v1 Announce Type: cross
Abstract: Multi-robot collaboration could enable more efficient and scalable solutions to complex robotic tasks, but collaboration under partial observability...
By Dorian Benhamou Goldfajn, Mason Nakamura, Saaduddin Mahmud, Justin Svegliato, Kyle H. Wray, Shlomo Zilberstein
arXiv:2607. 07357v1 Announce Type: cross Abstract: Effective social robot navigation requires sensitivity to human behavior, often revealed through subtle skeletal cues like gait and orientation.
By Daeun Song, Nhat Le, Jeffrey Chen, Mohammad Nazeri, Amirreza Payandeh, Rohan Chandra, Reuth Mirsky, Ross Mead, Ling Xiao, Xuesu Xiao
arXiv:2606. 18836v1 Announce Type: cross Abstract: Effective human-robot teamwork requires robots to adapt to partners, situations, and task dynamics from the start of an interaction.
By Taewoon Kim, Emma van Zoelen, Mark Neerincx
arXiv:2609.39665v1 Announce Type: new
Abstract: Embodied agents must determine where to act, anticipate the resulting scene changes, and interpret observed outcomes to guide subsequent actions. This...
By Chenyangguang Zhang, Malgorzata Gwiazda, Guanlong Jiao, Yuanchen Ju, Federico Tombari, Koushil Sreenath, Marc Pollefeys, Sunghwan Hong
arXiv:2512. 19178v2 Announce Type: replace-cross Abstract: Bridging the gap between natural language commands and autonomous execution in unstructured environments remains an open challenge for robotics.
By Jin Wang, Kim Tien Ly, Jacques Cloete, Jin Jin, Nikos Tsagarakis, Ioannis Havoutis
The thesis "Robotic Contextual Awareness for Human-Robot Collaboration and Environmental Understanding" addresses the challenge of enabling autonomous mobile robots to operate safely in dynamic, human-centric environments by developing advanced contextual awareness. It presents two complementary research directions: (1) a human re-identification and tracking system that allows a robot to recognize and collaborate with a specific person while ignoring others, and (2) enhanced perceptual capabilities that provide geometric and semantic understanding of the environment for improved motion planning and interaction. These contributions aim to improve robots’ knowledge of their surroundings, facilitating smoother and more natural collaboration with humans.
By Federico Rollo
arXiv:2602. 23312v3 Announce Type: replace-cross Abstract: Leader-follower interaction is an important paradigm in human-robot interaction (HRI).
By Rafael R. Baptista, Andr\'e de Lima Salgado, Ricardo V. Godoy, Marcelo Becker, Thiago Boaventura, Gustavo J. G. Lahr