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๐Ÿ” tom rainforth ๐Ÿ“‚ Engineering
Showing 722 results for "tom rainforth" in Engineering
Engineering Preprint PDF DOI

Closed Form Time Derivatives of the Equations of Motion of Rigid Body Systems

Andreas Mueller, Shivesh Kumar ยท 2025

Derivatives of equations of motion(EOM) describing the dynamics of rigid body systems are becoming increasingly relevant for the robotics community and find many applications in design and control of โ€ฆ

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Engineering Preprint PDF DOI

MolFORM: Preference-Aligned Multimodal Flow Matching for Structure-Based Drug Design

Daiheng Zhang, Zhao Zhang ยท 2025

Structure-based drug design (SBDD) aims to efficiently discover high-affinity ligands within vast chemical spaces. However, current generative models struggle with objective misalignment and rigid samโ€ฆ

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Engineering Preprint PDF DOI

Force-IMU Fusion-Based Sensing Acupuncture Needle and Quantitative Analysis System for Acupuncture Manipulations

Peng Tian, Kang Yu, Tianyun Jiang, Yuqi Wang, Haiying Zhang, Hao Yang, Yunfeng Wang, Jun Zhang, Shuo Gao, Junhong Gao ยท 2025

Acupuncture, one of the key therapeutic methods in Traditional Chinese Medicine (TCM), has been widely adopted in various clinical fields. Quantitative research on acupuncture manipulation parameters โ€ฆ

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Engineering Preprint PDF DOI

Ensemble Kalman Filter for Data Assimilation coupled with low-resolution computations techniques applied in Fluid Dynamics

Paul Jeanney, Ashton Hetherington, Shady E. Ahmed, David Lanceta, Susana Saiz, Jose Miguel Perez, Soledad Le Clainche ยท 2025

This paper presents an innovative Reduced-Order Model (ROM) for merging experimental and simulation data using Data Assimilation (DA) to estimate the "True" state of a fluid dynamics system, leading tโ€ฆ

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Engineering Preprint PDF DOI

Augmented Physics-Based Li-ion Battery Model via Adaptive Ensemble Sparse Learning and Conformal Prediction

Samuel Filgueira da Silva, Mehmet Fatih Ozkan, Faissal El Idrissi, Marcello Canova ยท 2025

Accurate electrochemical models are essential for the safe and efficient operation of lithium-ion batteries in real-world applications such as electrified vehicles and grid storage. Reduced-order modeโ€ฆ

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Engineering Preprint PDF DOI

Characterization of Rydberg-Atom Signal Reception of Dual-Frequency Signals Coupled with Two Energy Levels

Hao Wu, Chongwu Xie, Xinyuan Yao, Kang-Da Wu, Shanchi Wu, Rui Ni, Guo-Yong Xiang, Chen Gong ยท 2025

Rydberg atomic sensors have been adopted for novel radio frequency (RF) measurement technique and the sensing capability for signals in multiple frequencies makes it attractive for multi-user communicโ€ฆ

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Engineering Preprint PDF DOI

Investigating Lagrangian Neural Networks for Infinite Horizon Planning in Quadrupedal Locomotion

Prakrut Kotecha, Aditya Shirwatkar, Shishir Kolathaya ยท 2025

Lagrangian Neural Networks (LNNs) present a principled and interpretable framework for learning the system dynamics by utilizing inductive biases. While traditional dynamics models struggle with compoโ€ฆ

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Engineering Preprint PDF DOI

A Low-Cost Portable Lidar-based Mobile Mapping System on an Android Smartphone

Jianzhu Huai, Yuxin Shao, Yujia Zhang, Alper Yilmaz ยท 2025

The rapid advancement of the metaverse, digital twins, and robotics underscores the demand for low-cost, portable mapping systems for reality capture. Current mobile solutions, such as the Leica BLK2Gโ€ฆ

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Engineering Preprint PDF DOI

Adaptive Model-Base Control of Quadrupeds via Online System Identification using Kalman Filter

Jonas Haack, Franek Stark, Shubham Vyas, Frank Kirchner, Shivesh Kumar ยท 2025

Many real-world applications require legged robots to be able to carry variable payloads. Model-based controllers such as model predictive control (MPC) have become the de facto standard in research fโ€ฆ

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Engineering Preprint PDF DOI

Synesthesia of Machines (SoM)-Enhanced Sub-THz ISAC Transmission for Air-Ground Network

Zonghui Yang, Shijian Gao, Xiang Cheng, Liuqing Yang ยท 2025

Integrated sensing and communication (ISAC) within sub-THz frequencies is crucial for future air-ground networks, but unique propagation characteristics and hardware limitations present challenges in โ€ฆ

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Engineering Preprint PDF DOI

Explosive Output to Enhance Jumping Ability: A Variable Reduction Ratio Design Paradigm for Humanoid Robots Knee Joint

Xiaoshuai Ma, Haoxiang Qi, Qingqing Li, Haochen Xu, Xuechao Chen, Junyao Gao, Zhangguo Yu, Qiang Huang ยท 2025

Enhancing the explosive power output of the knee joints is critical for improving the agility and obstacle-crossing capabilities of humanoid robots. However, a mismatch between the knee-to-center-of-mโ€ฆ

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Engineering Preprint PDF DOI

Interpretable and flexible non-intrusive reduced-order models using reproducing kernel Hilbert spaces

Alejandro N Diaz, Shane A McQuarrie, John T Tencer, Patrick J Blonigan ยท 2025

This paper develops an interpretable, non-intrusive reduced-order modeling technique using regularized kernel interpolation. Existing non-intrusive approaches approximate the dynamics of a reduced-ordโ€ฆ

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Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration

Xiang Cheng, Boxun Liu, Xuanyu Liu, Ensong Liu, Ziwei Huang ยท 2025

To support future intelligent multifunctional sixth-generation (6G) wireless communication networks, Synesthesia of Machines (SoM) is proposed as a novel paradigm for artificial intelligence (AI)-natiโ€ฆ

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Engineering Preprint PDF DOI

Synesthesia of Machines (SoM)-Aided Online FDD Precoding via Heterogeneous Multi-Modal Sensing: A Vertical Federated Learning Approach

Haotian Zhang, Shijian Gao, Weibo Wen, Xiang Cheng, Liuqing Yang ยท 2025

This paper investigates a heterogeneous multi-vehicle, multi-modal sensing (H-MVMM) aided online precoding problem. The proposed H-MVMM scheme utilizes a vertical federated learning (VFL) framework toโ€ฆ

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Engineering Preprint PDF DOI

TD-TOG Dataset: Benchmarking Zero-Shot and One-Shot Task-Oriented Grasping for Object Generalization

Valerija Holomjova, Jamie Grech, Dewei Yi, Bruno Yun, Andrew Starkey, Pascal Mei{ss}ner ยท 2025

Task-oriented grasping (TOG) is an essential preliminary step for robotic task execution, which involves predicting grasps on regions of target objects that facilitate intended tasks. Existing literatโ€ฆ

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Engineering Preprint PDF DOI

Laterally Excited Bulk Acoustic Wave (LBAW) X-Cut Lithium Niobate Resonators

Walter Gubinelli, Ryan Tetro, Pietro Simeoni, Luca Colombo, Matteo Rinaldi ยท 2025

In this work, Laterally excited Bulk Acoustic Wave (LBAW) resonators on X-cut Lithium Niobate (LiNbO3) and, for the first time their higher-order overtones (LOBAW) are demonstrated by embedding interdโ€ฆ

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Engineering Preprint PDF DOI

Rydberg Atomic Quantum MIMO Receivers for The Multi-User Uplink

Tierui Gong, Chau Yuen, Chong Meng Samson See, Merouane Debbah, Lajos Hanzo ยท 2025

Rydberg atomic quantum receivers (RAQRs) have emerged as a promising solution for evolving wireless receivers from the classical to the quantum domain. To further unleash their great potential in wireโ€ฆ

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Engineering Preprint PDF DOI

COM Adjustment Mechanism Control for Multi-Configuration Motion Stability of Unmanned Deformable Vehicle

Jun Liu, Hongxun Liu, Cheng Zhang, Jiandang Xing, Shang Jiang, Ping Jiang ยท 2025

An unmanned deformable vehicle is a wheel-legged robot transforming between two configurations: vehicular and humanoid states, with different motion modes and stability characteristics. To address motโ€ฆ

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Engineering Preprint PDF DOI

GIT-BO: High-Dimensional Bayesian Optimization with Tabular Foundation Models

Rosen Ting-Ying Yu, Cyril Picard, Faez Ahmed ยท 2025

Bayesian optimization (BO) struggles in high dimensions, where Gaussian-process surrogates demand heavy retraining and brittle assumptions, slowing progress on real engineering and design problems. Weโ€ฆ

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Engineering Preprint PDF DOI

LLM4SG: Adapting Large Language Model for Scatterer Generation via Synesthesia of Machines

Zengrui Han, Lu Bai, Ziwei Huang, Xiang Cheng ยท 2025

In this paper, a novel large language model (LLM)-based method for scatterer generation (LLM4SG) is proposed for sixth-generation (6G) artificial intelligence (AI)-native communications. To provide a โ€ฆ

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