5 papers
Learning Tactile-Aware Quadrupedal Loco-Manipulation Policies
Pokuang Zhou, Yuhao Zhou, Quan Khanh Luu +7
Quadrupedal loco-manipulation is commonly built on visual perception and proprioception. Yet reliable contact-rich manipulation remains difficult: vision and proprioception alone c…
Imagining the Sense of Touch: Touch-Informed Manipulation via Imagined Tactile Representations
Zhiyuan Zhang, Adeesh Desai, Jyun-Chi Hu +7
Tactile sensing can substantially improve contact-rich robotic manipulation, yet its practical deployment remains limited by the fragility, calibration requirements, and maintenanc…
PLanAR: Planning-Language-Grounded Agentic Reasoning for Robot Manipulation
Pengyuan Guo, Zhonghao Mai, Zhengtong Xu +8
Recent advances in vision-language models (VLMs) have enabled increasing progress in real-world robot manipulation. However, long-horizon manipulation in unstructured environments…
ManiFeel: Benchmarking and Understanding Visuotactile Manipulation Policy Learning
Quan Khanh Luu, Pokuang Zhou, Zhengtong Xu +3
Supervised visuomotor policies have shown strong performance in robotic manipulation but often struggle in tasks with limited visual inputs, such as operations in confined spaces a…
Context-aware LLM-based Safe Control Against Latent Risks
Xiyu Deng, Quan Khanh Luu, Anh Van Ho +1
Autonomous control systems face significant challenges in performing complex tasks in the presence of latent risks. To address this, we propose an integrated framework that combine…