5 papers
RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning
Jinbang Huang, Yuanzhao Hu, Zhiyuan Li +6
Long-horizon robotic tasks require diverse capabilities that no single policy can reliably provide. Heterogeneous policies offer complementary strengths, but orchestrating them req…
Self-CriTeach: LLM Self-Teaching and Self-Critiquing for Improving Robotic Planning via Automated Domain Generation
Jinbang Huang, Zhiyuan Li, Yuanzhao Hu +4
Large Language Models (LLMs) have recently shown strong promise for robotic task planning, particularly through automatic planning domain generation. However, prior approaches larg…
H-WM: Robotic Task and Motion Planning Guided by Hierarchical World Model
Jinbang Huang, Wenyuan Chen, Zhiyuan Li +9
World models are becoming central to robotic planning and control as they enable prediction of future state transitions. Existing approaches often emphasize video generation or nat…
One Demo Is All It Takes: Planning Domain Derivation with LLMs from A Single Demonstration
Jinbang Huang, Yixin Xiao, Zhanguang Zhang +3
Pre-trained large language models (LLMs) show promise for robotic task planning but often struggle to guarantee correctness in long-horizon problems. Task and motion planning (TAMP…
Automated Planning Domain Inference for Task and Motion Planning
Jinbang Huang, Allen Tao, Rozilyn Marco +3
Task and motion planning (TAMP) frameworks address long and complex planning problems by integrating high-level task planners with low-level motion planners. However, existing TAMP…