From the 1 of 10 linked papers with an AI index.
10 papers
APPLV: Adaptive Planner Parameter Learning from Vision-Language-Action Model
Yuanjie Lu, Beichen Wang, Zhengqi Wu +4
The paper introduces APPLV, a system that uses vision‑language models to predict parameters for classical motion planners, combining safety of traditional planners with adaptabilit…
Improving Diffusion Planners by Self-Supervised Action Gating with Energies
Yuan Lu, Dongqi Han, Yansen Wang +1
Diffusion planners are a strong approach for offline reinforcement learning, but they can fail when value-guided selection favours trajectories that score well yet are locally inco…
CORAL: COntextual Reasoning And Local Planning in A Hierarchical VLM Framework for Underwater Monitoring
Zhenqi Wu, Yuanjie Lu, Xuesu Xiao +1
Oyster reefs are critical ecosystem species that sustain biodiversity, filter water, and protect coastlines, yet they continue to decline globally. Restoring these ecosystems requi…
Moving Through Clutter: Scaling Data Collection and Benchmarking for 3D Scene-Aware Humanoid Locomotion via Virtual Reality
Beichen Wang, Yuanjie Lu, Linji Wang +2
Recent advances in humanoid locomotion have enabled dynamic behaviors such as dancing, martial arts, and parkour, yet these capabilities are predominantly demonstrated in open, fla…
Adaptive Dynamics Planning for Robot Navigation
Yuanjie Lu, Mingyang Mao, Tong Xu +3
Autonomous robot navigation systems often rely on hierarchical planning, where global planners compute collision-free paths without considering dynamics, and local planners enforce…
Decremental Dynamics Planning for Robot Navigation
Yuanjie Lu, Tong Xu, Linji Wang +2
Most, if not all, robot navigation systems employ a decomposed planning framework that includes global and local planning. To trade-off onboard computation and plan quality, curren…