CoorDex: Coordinating Body and Hand Priors for Continuous Dexterous Humanoid Loco-Manipulation

Sikai Li, Shuning Li, Zhenyu Wei, Yunchao Yao, Chenran Li, Mingyu Ding

Paper Project Code

• We introduce CoorDex, a learning pipeline that converts high-dimensional body and dexterous hand control into coordinated latent residual control, enabling high-DoF dexterous loco-manipulation on the move.

AnyBody: Free-Form Whole-Body Humanoid Control from Arbitrary Keypoint Guidance

Shuning Li, Sikai Li, Jiachen Li, Mingyu Ding

Paper Project Code

• We present AnyBody, a unified whole-body humanoid controller driven by an arbitrary subset of body keypoints chosen at deploy time.

DexCompose: Reusing Dexterous Policies for Multi-Task Manipulation with a Single Hand

Dihong Huang, Zhenyu Wei, Zhuxiu Xu, Yunchao Yao, Sikai Li, Mingyu Ding

Paper Project Code

• We propose DexCompose, a role-aware residual composition framework that reuses pretrained dexterous policies for multi-task manipulation through explicit finger-level action ownership.

SldprtNet: A Large-Scale Multimodal Dataset for CAD Generation in Language-Driven 3D Design

Ruogu Li, Sikai Li, Yao Mu, Mingyu Ding

Paper

• We introduce SldprtNet, a large-scale dataset comprising over 242,000 industrial parts, designed for semanticdriven CAD modeling, geometric deep learning, and the training/fine-tuning of multimodal models for 3D design.

Tactile Functasets: Neural Implicit Representations of Tactile Datasets

Sikai Li, Samanta Rodriguez, Yiming Dou, Andrew Owens, Nima Fazeli

Paper Project Code

• Rather than directly using raw tactile images, we propose neural implicit functions trained to reconstruct the tactile dataset, producing compact representations that capture the underlying structure of the sensory inputs.

Communication and Verification in LLM Agents towards Collaboration under Information Asymmetry

Run Peng*, Ziqiao Ma*, Amy Pang, Sikai Li, Zhang Xi-Jia, Yingzhuo Yu, Cristian-Paul Bara, Joyce Chai

Paper Project Code

• We study LLM agents in task collaboration, particularly under the condition of information asymmetry, where agents have disparities in their knowledge and skills and need to work together to complete a shared task.

Think, Act, and Ask: Open-World Interactive Personalized Robot Navigation

Yinpei Dai, Run Peng, Sikai Li, Joyce Chai

Paper Video Code

• We propose a new framework termed Open-woRld Interactive persOnalized Navigation (ORION), which uses Large Language Models to make sequential decisions to manipulate different modules for perception, navigation and communication.

An Adaptive Path Planning Approach for Digital Twin-Enabled Robot Arm Based on Inverse Kinematics and Deep Reinforcement Learning

Qi Zhou, Sikai Li, Jingbo Qu, Jin Wu, Haomiao Xu, Youyi Bi

Paper

• We propose an adaptive path planning approach for robot arm based on Inverse Kinematics and Deep Reinforcement Learning in a pick-and-place context.

Adaptive Robot Motion Planning for Smart Manufacturing Based on Digital Twin and Bayesian Optimization-Enhanced Reinforcement Learning

Qi Zhou, Jin Wu, Boyan Li, Sikai Li, Bohan Feng, Jiangshan Liu, Youyi Bi

Paper

• An adaptive robot motion planning approach is proposed based on digital twin and reinforcement learning. The core idea is to adaptively select geometry-based or RL-based methods for robot motion planning through a real-time distance detection mechanism, which can reduce the complexity of RL model training and accelerate the training process.