7 citations · 7 across the 9 of their papers we have counts for
11 papers
CEER2: Directional and Tunable End-Effector and Root Compliance for Humanoid Loco-Manipulation
Xinyuan Luo, Chunyuan Yang, Boyuan Chen +1
Humanoids are increasingly capable of tracking complex whole-body motions, but physical interaction introduces a different challenge. When a robot makes contact with a person or th…
FRAMES: Failure Recovery And Monitoring of Embodied Skills for Humanoid Loco-Manipulation
Ajay Vikram Periasami, Xinyuan Luo, Haoyu Li +1
Large language model (LLM) planners can decompose natural-language instructions and select reusable robot skills, but choosing the correct skill does not guarantee successful physi…
Robustness of Robotic Manipulation: Foundations and Frontiers
Yifei Dong, Zhanyi Sun, Lujie Yang +5
Humans and animals exhibit remarkable robustness in physical manipulation, yet robots remain far behind. Progress toward human-level manipulation robustness is hindered by the abse…
PhysGraph: A Physics-aware 3D Scene Graph for Perception and Reasoning
Haoyu Li, Aaron Thomas, Shuyan Zhou +1
To perform a wide range of daily tasks, robots need to construct a 3D representation that is semantically rich, physically grounded, and structured enough to support task planning…
Any-ttach: Quick End-effector Swapping Enables Manipulation Dexterity with Simplicity
Weizhe Ni, Jinzhou Li, Haoyu Li +3
Robotic manipulation dexterity is often pursued by building increasingly complex high-DoF multifingered hands. While many robotic hands are designed to replicate human morphology,…
CEER: Compliant End-Effector and Root Control as a Unified Interface for Hierarchical Humanoid Loco-Manipulation
Xinyuan Luo, Xingrui Chen, Xunjian Yin +6
Humanoid robots have achieved impressive locomotion performance, yet contact-rich and long-horizon manipulation remains a major bottleneck. Manipulation is inherently contact-rich…
On Safety Risks in Experience-Driven Self-Evolving Agents
Weixiang Zhao, Yichen Zhang, Yingshuo Wang +8
Experience-driven self-evolution has emerged as a promising paradigm for improving the autonomy of large language model agents, yet its reliance on self-curated experience introduc…
OPENTOUCH: Bringing Full-Hand Touch to Real-World Interaction
Yuxin Ray Song, Jinzhou Li, Rao Fu +12
The human hand is our primary interface to the physical world, yet egocentric perception rarely knows when, where, or how forcefully it makes contact. Robust wearable tactile senso…
Humanoid Locomotion and Manipulation: Current Progress and Challenges in Control, Planning, and Learning
Zhaoyuan Gu, Junheng Li, Wenlan Shen +15
Humanoid robots hold great potential to perform various human-level skills, involving unified locomotion and manipulation in real-world settings. Driven by advances in machine lear…
CageCoOpt: Enhancing Manipulation Robustness through Caging-Guided Morphology and Policy Co-Optimization
Yifei Dong, Shaohang Han, Xianyi Cheng +5
Uncertainties in contact dynamics and object geometry remain significant barriers to robust robotic manipulation. Caging mitigates these uncertainties by constraining an object's m…
Characterizing Manipulation Robustness through Energy Margin and Caging Analysis
Yifei Dong, Xianyi Cheng, Florian T. Pokorny
To develop robust manipulation policies, quantifying robustness is essential. Evaluating robustness in general manipulation, nonetheless, poses significant challenges due to comple…