activity
20242026
most citedGRaD-Nav++: Vision-Language Model Enabled Visual Drone Navigation with Gaussian Radiance Fields and Differentiable Dynamics

1 citations · 1 across the 8 of their papers we have counts for

collaborators
Showing cs.ROShow all

13 papers · 1 filter

cs.RO2026

PRIMAL3: Pathfinding via Reinforcement and Imitation Multi-Agent Learning - Leveraging LaCAM3

Chengyang He, Tanishq Duhan, Gadiel Sznaier Camps +6

We present PRIMAL3, an ultra-large-scale learning-based framework for multi-agent pathfinding (MAPF) that integrates reinforcement learning, topology-aware communication, LaCAM3-gu…

cs.RO20261 cited

GRaD-Nav++: Vision-Language Model Enabled Visual Drone Navigation with Gaussian Radiance Fields and Differentiable Dynamics

Qianzhong Chen, Naixiang Gao, Suning Huang +4

Autonomous drones capable of interpreting and executing high-level language instructions in unstructured environments remain a long-standing goal. Yet existing approaches are const…

cs.RO2026

Breaking Lock-In: Preserving Steerability under Low-Data VLA Post-Training

Suning Huang, Jiaqi Shao, Ke Wang +5

Have you ever post-trained a generalist vision-language-action (VLA) policy on a small demonstration dataset, only to find that it stops responding to new instructions and is limit…

cs.RO2026

, But Make It Fly: Physics-Guided Transfer of VLA Models to Aerial Manipulation

Johnathan Tucker, Denis Liu, Aiden Swann +7

Vision-Language-Action (VLA) models such as have demonstrated remarkable generalization across diverse fixed-base manipulators. However, transferring these foundation models…

cs.RO2026

SteerVLA: Steering Vision-Language-Action Models in Long-Tail Driving Scenarios

Tian Gao, Celine Tan, Catherine Glossop +8

A fundamental challenge in autonomous driving is the integration of high-level, semantic reasoning for long-tail events with low-level, reactive control for robust driving. While l…

cs.RO2025

ARCH: Hierarchical Hybrid Learning for Long-Horizon Contact-Rich Robotic Assembly

Jiankai Sun, Aidan Curtis, Yang You +8

Generalizable long-horizon robotic assembly requires reasoning at multiple levels of abstraction. While end-to-end imitation learning (IL) is a promising approach, it typically req…