activity
20222026
most citedTeamCraft: A Benchmark for Multi-Modal Multi-Agent Systems in Minecraft

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Learning to Absorb Corrections: Critic-Weighted Residual Flow for Vision-Based Insertion

Yiqing Yuan, Zhi Li, Jinrong Yang +5

Vision-based insertion requires correcting alignment errors while retaining useful behavior learned from demonstrations. We present ACT--Flow, an online learning framework that cou…

cs.RO2026

Unordered Landmark Visual Navigation

Hao Ren, Junzhe Zhu, Yihan Li +8

Image-goal navigation is a fundamental capability for embodied AI, yet its practical deployment is strained by strong prior assumptions. Existing methods predominantly rely on temp…

cs.RO2026

Fisher-Preserving Guidance: Training-Free Manifold Constraints for Safe Diffusion Control

Hao Ren, Zetong Bi, Yiming Zeng +5

Diffusion models are effective for waypoint prediction in visual navigation, but standard sampling and test time guidance can produce unreliable or inefficient trajectories when up…

cs.RO2026

Human-in-the-Loop Failure Recovery with Adaptive Task Allocation

Lorena Maria Genua, Nikita Boguslavskii, Zhi Li

Since the recent Covid-19 pandemic, mobile manipulators and humanoid assistive robots with higher levels of autonomy have increasingly been adopted for patient care and living assi…

cs.AI2024★ 1 cited

TeamCraft: A Benchmark for Multi-Modal Multi-Agent Systems in Minecraft

Qian Long, Zhi Li, Ran Gong +3

Collaboration is a cornerstone of society. In the real world, human teammates make use of multi-sensory data to tackle challenging tasks in ever-changing environments. It is essent…

cs.RO2024

Reactive Multi-Robot Navigation in Outdoor Environments Through Uncertainty-Aware Active Learning of Human Preference Landscape

Chao Huang, Wenshuo Zang, Carlo Pinciroli +4

Compared with single robots, Multi-Robot Systems (MRS) can perform missions more efficiently due to the presence of multiple members with diverse capabilities. However, deploying a…

cs.LG2022

Energy Management of Multi-mode Hybrid Electric Vehicles based on Hand-shaking Multi-agent Learning

Min Hua, Zhi Li, Quan Zhou

The future transportation system will be a multi-agent network where connected AI agents can work together to address the grand challenges in our age, e.g., mitigation of real-worl…