2 citations · 4 across the 5 of their papers we have counts for
6 papers
CABTO: Context-Aware Behavior Tree Grounding for Robot Manipulation
Yishuai Cai, Xinglin Chen, Yunxin Mao +6
Behavior Trees (BTs) offer a powerful paradigm for designing modular and reactive robot controllers. BT planning, an emerging field, provides theoretical guarantees for the automat…
DexFlyWheel: A Scalable and Self-improving Data Generation Framework for Dexterous Manipulation
Kefei Zhu, Fengshuo Bai, YuanHao Xiang +8
Dexterous manipulation is critical for advancing robot capabilities in real-world applications, yet diverse and high-quality datasets remain scarce. Existing data collection method…
MRBTP: Efficient Multi-Robot Behavior Tree Planning and Collaboration
Yishuai Cai, Xinglin Chen, Zhongxuan Cai +4
Multi-robot task planning and collaboration are critical challenges in robotics. While Behavior Trees (BTs) have been established as a popular control architecture and are plannabl…
Integrating Intent Understanding and Optimal Behavior Planning for Behavior Tree Generation from Human Instructions
Xinglin Chen, Yishuai Cai, Yunxin Mao +4
Robots executing tasks following human instructions in domestic or industrial environments essentially require both adaptability and reliability. Behavior Tree (BT) emerges as an a…
HBTP: Heuristic Behavior Tree Planning with Large Language Model Reasoning
Yishuai Cai, Xinglin Chen, Yunxin Mao +4
Behavior Trees (BTs) are increasingly becoming a popular control structure in robotics due to their modularity, reactivity, and robustness. In terms of BT generation methods, BT pl…
Task2Morph: Differentiable Task-inspired Framework for Contact-Aware Robot Design
Yishuai Cai, Shaowu Yang, Minglong Li +4
Optimizing the morphologies and the controllers that adapt to various tasks is a critical issue in the field of robot design, aka. embodied intelligence. Previous works typically m…