2 citations · 2 across the 7 of their papers we have counts for
5 papers · 1 filter
HM3D-M3: A Benchmark for Multi-Agent, Multi-Modal, Multi-Object Goal Navigation
Hongyu Ding, Kanyu Xu, Mingjia Chen +5
Rapid progress in AI agents and robotics makes it a matter of the near future that humans are served by a team of robots. Such a team will receive several goals at once, each speci…
HAM-VLN: Harnessing Hierarchical Agentic Memory for Zero-Shot Vision-and-Language Navigation
An Liu, Bingxi Liu, Hongyu Ding +6
Vision-and-language navigation (VLN) enables robots to follow instructions in previously unseen environments. Recently, a training-free paradigm has emerged: the robot queries a mu…
Uni-LaViRA: Language-Vision-Robot Actions Translation for Unified Embodied Navigation
Hongyu Ding, Sizhuo Zhang, Ziming Xu +13
Embodied navigation requires an agent to map language and visual observations to a stream of spatial actions that drive a real robot through environments it has never seen. The dom…
V-Dreamer: Automating Robotic Simulation and Trajectory Synthesis via Video Generation Priors
Songjia He, Zixuan Chen, Hongyu Ding +5
Training generalist robots demands large-scale, diverse manipulation data, yet real-world collection is prohibitively expensive, and existing simulators are often constrained by fi…
MoMaStage: Skill-State Graph Guided Planning and Closed-Loop Execution for Long-Horizon Indoor Mobile Manipulation
Chenxu Li, Zixuan Chen, Yetao Li +5
Long-horizon indoor mobile manipulation (MoMa) requires robots to execute extended navigation-manipulation sequences whose feasibility depends on state changes induced by preceding…