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Chenghao Wang

6 accepted papers

2025

Dynamic Quadrupedal Legged and Aerial Locomotion via Structure Repurposing

Chenghao Wang, Kaushik Venkatesh Krishnamurthy, Shreyansh Pitroda, Adarsh Salagame, Ioannis Mandralis, Eric Sihite +2
IROS 2025

Multi-modal ground-aerial robots have been extensively studied, with a significant challenge lying in the integration of conflicting requirements across different modes of operation. The Husky robot family, developed at North-eastern University, and specifically the Husky v.2 discussed in this study

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2025

Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoning

Rujing Yao, Yang Wu, Chenghao Wang, Jingwei Xiong, Fang Wang, Xiaozhong Liu
NAACL 2025long

Large Language Models (LLMs) have achieved impressive results across numerous domains, yet they experience notable deficiencies in legal question-answering tasks. LLMs often generate generalized responses that lack the logical specificity required for expert legal advice and are prone to hallucinati…

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2025

Learning Efficient and Robust Language-Conditioned Manipulation Using Textual-Visual Relevancy and Equivariant Language Mapping

Mingxi Jia, Haojie Huang, Zhewen Zhang, Chenghao Wang, Linfeng Zhao, Dian Wang +4
RA-L 2025

Controlling robots through natural language is pivotal for enhancing human-robot collaboration and synthesizing complex robot behaviors. Recent works that are trained on large robot datasets show impressive generalization abilities. However, such pretrained methods are (1) often fragile to unseen sc

Cited by 7Source ↗code ↗Scholar ↗
2025

Thruster-Enhanced Locomotion: A Decoupled Model Predictive Control with Learned Contact Residuals

Chenghao Wang, Alireza Ramezani
IROS 2025

Husky Carbon, a robot developed by Northeastern University, serves as a research platform to explore unification of posture manipulation and thrust vectoring. Unlike conventional quadrupeds, its joint actuators and thrusters enable enhanced control authority, facilitating thruster-assisted narrow-pa

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2024

Knowledge-Infused Legal Wisdom: Navigating LLM Consultation through the Lens of Diagnostics and Positive-Unlabeled Reinforcement Learning

Yang Wu, Chenghao Wang, Ece Gumusel, Xiaozhong Liu
ACL 2024findings

The integration of generative Large Language Models (LLMs) into various applications, including the legal domain, has been accelerated by their expansive and versatile nature. However, when facing a legal case, users without a legal background often struggle to formulate professional queries and may…

Cited by 7Source ↗PDF ↗code ↗Scholar ↗
2024

OrbitGrasp: SE(3)-Equivariant Grasp Learning

Boce Hu, Xupeng Zhu, Dian Wang, Zihao Dong, Haojie Huang, Chenghao Wang +2
CoRL 2024poster

While grasp detection is an important part of any robotic manipulation pipeline, reliable and accurate grasp detection in $\\mathrm{SE}(3)$ remains a research challenge. Many robotics applications in unstructured environments such as the home or warehouse would benefit a lot from better grasp perfor…

Cited by 13Source ↗code ↗Scholar ↗