arXiv:2607. 20785v1 Announce Type: cross Abstract: Deploying navigation systems at scale requires a recipe that minimizes sensor assumptions, generalizes across robot embodiments, and trains efficiently.
By Arjun Majumdar, Avinash Sooriyarachchi, Benjamin Tibi, Chris Bamford, Elliot Chane-Sane, Guillaume Lample, Khyathi Raghavi Chandu, Ludovic Ho Fuh, Mathieu Poiree, Olivier Duchenne, Rosalie Millner, Srijan Mishra, Theo Cachet, Thomas Chabal
arXiv:2606. 12352v1 Announce Type: cross Abstract: Multi-robot collaboration allows robots to efficiently take on a wide range of tasks, from moving a couch through a doorway to assembling structures on a construction site.
By Ria Doshi, Tian Gao, Annie Chen, Chelsea Finn, Jeannette Bohg
Robots deployed in delivery, campus, and emergency-response settings often need to navigate from buildings to streets within a single continuous episode. Existing benchmarks usually evaluate indoor and outdoor navigation separately, and many abstract away robot execution, leaving exit finding, boundary traversal, adaptation, and kinodynamic failures underexplored.
arXiv:2609.24576v1 Announce Type: cross
Abstract: Modern Vision-Language Navigation (VLN) models rely mostly on pre-trained large Vision-Language Models (VLMs) to predict navigation actions. While th...
By D\'ebora Oliveira Makowski, Samiran Gode, Abhijeet Nayak, Marco Hutter, Cordelia Schmid, Lukas Rosenberger Schmid, Wolfram Burgard
arXiv:2609.35965v1 Announce Type: cross
Abstract: Vision-and-Language Navigation (VLN) has largely focused on a single agent following a single instruction, yet many real-world applications require t...
By Yunzhe Xu, Zhe Liu
Navi-Agent is a zero‑shot Vision‑Language Navigation in Continuous Environments (VLN‑CE) agent that builds a coordinate‑free spatial state from visual observations and motion history. It represents this state as a navigation topology with nodes as visual places and edges as motion transitions, enabling observation‑based self‑localization, task progress verification, and recovery. Experiments on a zero‑shot VLN‑CE benchmark and real‑world robot platforms demonstrate that Navi‑Agent achieves state‑of‑the‑art performance among geometry‑constrained methods while remaining competitive with geometry‑based approaches.
By Wenyuan Xie, Mengyang Hong, Yongzhong Wang, Yanbiao Ji, Yijin Zhou, Shaokai Wu, Shalayiding Sirejiding, Huayi Zhou, Yi-Chao Chen, Ma Ling, Yue Ding, Hongtao Lu