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๐Ÿ” kai wu ๐Ÿ“‚ Engineering
Showing 151 results for "kai wu" in Engineering
Engineering Preprint PDF DOI

Path Integral Control for Partially Observed Systems with Controlled Sensing

Goutam Das, Takashi Tanaka ยท 2026

Path integral control in Gaussian belief space requires a structural matching condition between the observation-driven diffusion of the belief mean and the actuation authority, which a fixed observatiโ€ฆ

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Engineering Preprint PDF DOI

Data-Driven Reachability Analysis Using Matrix Perturbation Theory

Peng Xie, Abdulla Fawzy, Zhen Zhang, Amr Alanwar ยท 2026

We propose a matrix zonotope perturbation framework that leverages matrix perturbation theory to characterize how noise-induced distortions alter the dynamics within sets of models. The framework deriโ€ฆ

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Engineering Preprint PDF DOI

Path Integral Control in Gaussian Belief Space for Partially Observed Systems

Goutam Das, Takashi Tanaka ยท 2026

This paper extends path integral control (PIC) to partially observed systems by formulating the problem in Gaussian belief space. PIC relies on the diffusion being proportional to the control channel โ€ฆ

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Engineering Preprint PDF DOI

APEG: Adaptive Physical Layer Authentication with Channel Extrapolation and Generative AI

Xiqi Cheng, Rui Meng, Xiaodong Xu, Haixiao Gao, Ping Zhang, Dusit Niyato ยท 2026

With the rapid advancement of 6G, identity authentication has become increasingly critical for ensuring wireless security. The lightweight and keyless Physical Layer Authentication (PLA) is regarded aโ€ฆ

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Engineering Preprint PDF DOI

RoCo Challenge at AAAI 2026: Benchmarking Robotic Collaborative Manipulation for Assembly Towards Industrial Automation

Haichao Liu, Yuheng Zhou, Zhenyu Wu, Ziheng Ji, Ziyu Shan, Qianzhun Wang, Ruixuan Liu, Zhiyuan Yang, Yejun Gu, Shalman Khan, Shijun Yan, Jun Liu, Haiyue Zhu, Changliu Liu, Jianfei Yang, Jingbing Zhang, Ziwei Wang ยท 2026

Embodied Artificial Intelligence (EAI) is rapidly developing, gradually subverting previous autonomous systems' paradigms from isolated perception to integrated, continuous action. This transition is โ€ฆ

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Engineering Preprint PDF DOI

KAN-Koopman Based Rapid Detection Of Battery Thermal Anomalies With Diagnostics Guarantees

Sanchita Ghosh, Tanushree Roy ยท 2026

Early diagnosis of battery thermal anomalies is crucial to ensure safe and reliable battery operation by preventing catastrophic thermal failures. Battery diagnostics primarily rely on battery surfaceโ€ฆ

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Engineering Preprint PDF DOI

KAN We Flow? Advancing Robotic Manipulation with 3D Flow Matching via KAN & RWKV

Zhihao Chen, Yiyuan Ge, Ziyang Wang ยท 2026

Diffusion-based visuomotor policies excel at modeling action distributions but are inference-inefficient, since recursively denoising from noise to policy requires many steps and heavy UNet backbones,โ€ฆ

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Engineering Preprint PDF DOI

CM-GAI: Continuum Mechanistic Generative Artificial Intelligence Theory for Data Dynamics

Shan Tang, Ziwei Cao, Zhenling Yang, Jiachen Guo, Yicheng Lu, Wing Kam Liu, Xu Guo ยท 2026

Generative artificial intelligence (GAI) plays a fundamental role in high-impact AI-based systems such as SORA and AlphaFold. Currently, GAI shows limited capability in the specialized domains due to โ€ฆ

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Engineering Preprint PDF DOI

KAN-AE with Non-Linearity Score and Symbolic Regression for Energy-Efficient Channel Coding

Anthony Joseph Perre, Parker Huggins, Alphan Sahin ยท 2026

In this paper, we investigate Kolmogorov-Arnold network-based autoencoders (KAN-AEs) with symbolic regression (SR) for energy-efficient channel coding. By using SR, we convert KAN-AEs into symbolic exโ€ฆ

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Engineering Preprint PDF DOI

Learning to Anchor Visual Odometry: KAN-Based Pose Regression for Planetary Landing

Xubo Luo, Zhaojin Li, Xue Wan, Wei Zhang, Leizheng Shu ยท 2025

Accurate and real-time 6-DoF localization is mission-critical for autonomous lunar landing, yet existing approaches remain limited: visual odometry (VO) drifts unboundedly, while map-based absolute loโ€ฆ

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Engineering Preprint PDF DOI

Lyapunov-Based Kolmogorov-Arnold Network (KAN) Adaptive Control

Xuehui Shen, Wenqian Xue, Yixuan Wang, Warren E. Dixon ยท 2025

Recent advancements in Lyapunov-based Deep Neural Networks (Lb-DNNs) have demonstrated improved performance over shallow NNs and traditional adaptive control for nonlinear systems with uncertain dynamโ€ฆ

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Engineering Preprint PDF DOI

Deep learning water-unsuppressed MRSI at ultra-high field for simultaneous quantitative metabolic, susceptibility and myelin water imaging

Paul J. Weiser, Jiye Kim, Jongho Lee, Amirmohammad Shamaei, Gulnur Ungan, Malte Hoffmann, Antoine Klauser, Berkin Bilgic, Ovidiu C. Andronesi ยท 2025

Purpose: Magnetic Resonance Spectroscopic Imaging (MRSI) maps endogenous brain metabolism while suppressing the overwhelming water signal. Water-unsuppressed MRSI (wu-MRSI) allows simultaneous imagingโ€ฆ

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Engineering Preprint PDF DOI

A Model-Based Approach to Automated Digital Twin Generation in Manufacturing

Angelos Alexopoulos, Agorakis Bompotas, Nikitas Rigas Kalogeropoulos, Panagiotis Kechagias, Athanasios P. Kalogeras, Christos Alexakos ยท 2025

Modern manufacturing demands high flexibility and reconfigurability to adapt to dynamic production needs. Model-based Engineering (MBE) supports rapid production line design, but final reconfigurationโ€ฆ

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PFEA: An LLM-based High-Level Natural Language Planning and Feedback Embodied Agent for Human-Centered AI

Wenbin Ding, Jun Chen, Mingjia Chen, Fei Xie, Qi Mao, Philip Dames ยท 2025

The rapid advancement of Large Language Models (LLMs) has marked a significant breakthrough in Artificial Intelligence (AI), ushering in a new era of Human-centered Artificial Intelligence (HAI). HAI โ€ฆ

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Semantic Intelligence: A Bio-Inspired Cognitive Framework for Embodied Agents

Wenbing Tang, Meilin Zhu, Fenghua Wu, Yang Liu ยท 2025

Recent advancements in Large Language Models (LLMs) have greatly enhanced natural language understanding and content generation. However, these models primarily operate in disembodied digital environmโ€ฆ

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Engineering Preprint PDF DOI

NeMo-map: Neural Implicit Flow Fields for Spatio-Temporal Motion Mapping

Yufei Zhu, Shih-Min Yang, Andrey Rudenko, Tomasz P. Kucner, Achim J. Lilienthal, Martin Magnusson ยท 2025

Safe and efficient robot operation in complex human environments can benefit from good models of site-specific motion patterns. Maps of Dynamics (MoDs) provide such models by encoding statistical motiโ€ฆ

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Engineering Preprint PDF DOI

Progressive Uncertainty-Guided Evidential U-KAN for Trustworthy Medical Image Segmentation

Zhen Yang, Yansong Ma, Lei Chen ยท 2025

Trustworthy medical image segmentation aims at deliver accurate and reliable results for clinical decision-making. Most existing methods adopt the evidence deep learning (EDL) paradigm due to its compโ€ฆ

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Engineering Preprint PDF DOI

Long-Term Human Motion Prediction Using Spatio-Temporal Maps of Dynamics

Yufei Zhu, Andrey Rudenko, Tomasz P. Kucner, Achim J. Lilienthal, Martin Magnusson ยท 2025

Long-term human motion prediction (LHMP) is important for the safe and efficient operation of autonomous robots and vehicles in environments shared with humans. Accurate predictions are important for โ€ฆ

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Engineering Preprint PDF DOI

Mutual Information-Driven Visualization and Clustering for Core KPI Selection in O-RAN Testing

Anish Pradhan, Lingjia Liu, Harpreet S. Dhillon ยท 2025

O-RAN testing is becoming increasingly difficult with the exponentially growing number of performance measurements as the system grows more complex, with additional units, interfaces, applications, anโ€ฆ

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Engineering Preprint PDF DOI

NAMOUnc: Navigation Among Movable Obstacles with Decision Making on Uncertainty Interval

Kai Zhang, Eric Lucet, Julien Alexandre Dit Sandretto, Shoubin Chen, David Filliat ยท 2025

Navigation among movable obstacles (NAMO) is a critical task in robotics, often challenged by real-world uncertainties such as observation noise, model approximations, action failures, and partial obsโ€ฆ

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