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๐Ÿ” avoidance learning ๐Ÿ“‚ Engineering
Showing 39379 results for "avoidance learning" in Engineering
Engineering Preprint PDF DOI

Trustworthy Evaluation of Robotic Manipulation: A New Benchmark and AutoEval Methods

Mengyuan Liu, Juyi Sheng, Peiming Li, Ziyi Wang, Tianming Xu, Tiantian Xu, Hong Liu ยท 2026

Driven by the rapid evolution of Vision-Action and Vision-Language-Action models, imitation learning has significantly advanced robotic manipulation capabilities. However, evaluation methodologies havโ€ฆ

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Engineering Preprint PDF DOI

A Pragmatic VLA Foundation Model

Wei Wu, Fan Lu, Yunnan Wang, Shuai Yang, Shi Liu, Fangjing Wang, Qian Zhu, He Sun, Yong Wang, Shuailei Ma, Yiyu Ren, Kejia Zhang, Hui Yu, Jingmei Zhao, Shuai Zhou, Zhenqi Qiu, Houlong Xiong, Ziyu Wang, Zechen Wang, Ran Cheng, Yong-Lu Li, Yongtao Huang, Xing Zhu, Yujun Shen, Kecheng Zheng ยท 2026

Offering great potential in robotic manipulation, a capable Vision-Language-Action (VLA) foundation model is expected to faithfully generalize across tasks and platforms while ensuring cost efficiencyโ€ฆ

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Engineering Preprint PDF DOI

ExoGS: A 4D Real-to-Sim-to-Real Framework for Scalable Manipulation Data Collection

Yiming Wang, Ruogu Zhang, Minyang Li, Hao Shi, Junbo Wang, Deyi Li, Jieji Ren, Wenhai Liu, Weiming Wang, Hao-Shu Fang ยท 2026

Real-to-Sim-to-Real technique is gaining increasing interest for robotic manipulation, as it can generate scalable data in simulation while having narrower sim-to-real gap. However, previous methods mโ€ฆ

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Engineering Preprint PDF DOI

Regulatory Hub Discovery in MDD Methylome: Hypotheses for Molecular Subtypes via Computational Analysis

Mingyan Liu, Min Huang ยท 2026

Major Depressive Disorder (MDD) is a clinically heterogeneous syndrome with diverse etiological pathways. Traditional Epigenome-Wide Association Studies (EWAS) have successfully identified risk loci bโ€ฆ

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Engineering Preprint PDF DOI

Real-Time Prediction of Lower Limb Joint Kinematics, Kinetics, and Ground Reaction Force using Wearable Sensors and Machine Learning

Josee Mallah, Yu Zhu, Kailang Xu, Gurvinder S. Virk, Shaoping Bai, Luigi G. Occhipinti ยท 2026

Walking is a key movement of interest in biomechanics, yet gold-standard data collection methods are time- and cost-expensive. This paper presents a real-time, multimodal, high sample rate lower-limb โ€ฆ

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Engineering Preprint PDF DOI

Dynamic Channel Charting: An LSTM-AE-based Approach

Yuan Gao, Wenjing Xie, Yiming Liu, Bintao Hu, Jianbo Du, Shugong Xu ยท 2026

With the development of the sixth-generation (6G) communication system, Channel State Information (CSI) plays a crucial role in improving network performance. Traditional Channel Charting (CC) methodsโ€ฆ

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Engineering Preprint PDF DOI

Deep Reinforcement Learning for Hybrid RIS Assisted MIMO Communications

Phuong Nam Tran, Nhan Thanh Nguyen, Markku Juntti ยท 2026

Hybrid reconfigurable intelligent surfaces (HRIS) enhance wireless systems by combining passive reflection with active signal amplification. However, jointly optimizing the transmit beamforming with tโ€ฆ

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Engineering Preprint PDF DOI

Residual Learning for Neural Ambisonics Encoders

Thomas Deppisch, Yang Gao, Manan Mittal, Benjamin Stahl, Christoph Hold, David Alon, Zamir Ben-Hur ยท 2026

Emerging wearable devices such as smartglasses and extended reality headsets demand high-quality spatial audio capture from compact, head-worn microphone arrays. Ambisonics provides a device-agnostic โ€ฆ

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Engineering Preprint PDF DOI

Convex Chance-Constrained Stochastic Control under Uncertain Specifications with Application to Learning-Based Hybrid Powertrain Control

Teruki Kato, Ryotaro Shima, Kenji Kashima ยท 2026

This paper presents a strictly convex chance-constrained stochastic control framework that accounts for uncertainty in control specifications such as reference trajectories and operational constraintsโ€ฆ

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Engineering Preprint PDF DOI

Gradient-Informed Machine Learning in Electromagnetics

Matteo Zorzetto, Merle Backmeyer, Michael Wiesheu, Riccardo Torchio, Fabrizio Dughiero, Sebastian Schops ยท 2026

Simulation techniques such as the finite element method are essential for designing electrical devices, but their computational cost can be prohibitive for repeated or real-time computations. Projectiโ€ฆ

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Engineering Preprint PDF DOI

Noise-Robust Contrastive Learning with an MFCC-Conformer For Coronary Artery Disease Detection

Milan Marocchi, Matthew Fynn, Yue Rong ยท 2026

Cardiovascular diseases (CVD) are the leading cause of death worldwide, with coronary artery disease (CAD) comprising the largest subcategory of CVDs. Recently, there has been increased focus on detecโ€ฆ

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Engineering Preprint PDF DOI

Reinforcement Learning with Distributed MPC for Fuel-Efficient Platoon Control with Discrete Gear Transitions

Samuel Mallick, Gianpietro Battocletti, Dimitris Boskos, Azita Dabiri, Bart De Schutter ยท 2026

Cooperative control of groups of autonomous vehicles (AVs), i.e., platoons, is a promising direction to improving the efficiency of autonomous transportation systems. In this context, distributed co-oโ€ฆ

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Engineering Preprint PDF DOI

Efficient Rehearsal for Continual Learning in ASR via Singular Value Tuning

Steven Vander Eeckt, Hugo Van hamme ยท 2026

Continual Learning (CL) in Automatic Speech Recognition (ASR) suffers from catastrophic forgetting when adapting to new tasks, domains, or speakers. A common strategy to mitigate this is to store a suโ€ฆ

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Engineering Preprint PDF DOI

Grasp-and-Lift: Executable 3D Hand-Object Interaction Reconstruction via Physics-in-the-Loop Optimization

Byeonggyeol Choi, Woojin Oh, Jongwoo Lim ยท 2026

Dexterous hand manipulation increasingly relies on large-scale motion datasets with precise hand-object trajectory data. However, existing resources such as DexYCB and HO3D are primarily optimized forโ€ฆ

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Engineering Preprint PDF DOI

Data-driven nonparametric Li-ion battery ageing model aiming at learning from real operation data -- Part B: Cycling operation

Lucu M., Martinez-Laserna E., Gandiaga I., Liu K., Camblong H., Widanage W.D., Marco J ยท 2026

Conventional Li-ion battery ageing models, such as electrochemical, semi-empirical and empirical models, require a significant amount of time and experimental resources to provide accurate predictionsโ€ฆ

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Engineering Preprint PDF DOI

Data-driven nonparametric Li-ion battery ageing model aiming at learning from real operation data -- Part A: Storage operation

Lucu M., Martinez-Laserna E., Gandiaga I., Liu K., Camblong H., Widanage W.D., Marco J ยท 2026

Conventional Li-ion battery ageing models, such as electrochemical, semi-empirical and empirical models, require a significant amount of time and experimental resources to provide accurate predictionsโ€ฆ

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Engineering Preprint PDF DOI

Energy-Aware Reinforcement Learning for Robotic Manipulation of Articulated Components in Infrastructure Operation and Maintenance

Xiaowen Tao, Yinuo Wang, Haitao Ding, Yuanyang Qi, Ziyu Song ยท 2026

With the growth of intelligent civil infrastructure and smart cities, operation and maintenance (O&M) increasingly requires safe, efficient, and energy-conscious robotic manipulation of articulated coโ€ฆ

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Engineering Preprint PDF DOI

A Physics-Informed Digital Twin Framework for Calibrated Sim-to-Real FMCW Radar Occupancy Estimation

Huy Trinh, Sebastian Ratto V, Elliot Creager, George Shaker ยท 2026

Learning robust radar perception models directly from real measurements is costly due to the need for controlled experiments, repeated calibration, and extensive annotation. This paper proposes a lighโ€ฆ

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Engineering Preprint PDF DOI

Less Is More: Scalable Visual Navigation from Limited Data

Yves Inglin, Jonas Frey, Changan Chen, Marco Hutter ยท 2026

Imitation learning provides a powerful framework for goal-conditioned visual navigation in mobile robots, enabling obstacle avoidance while respecting human preferences and social norms. However, its โ€ฆ

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Engineering Preprint PDF DOI

OCTA-Based Biomarker Characterization in nAMD

MAria Simona Tivadar, Ioana Damian, Adrian Groza, Simona Delia Nicoara ยท 2026

We aim to enhance ophthalmologists' decision-making when diagnosing the Neovascular Age-Related Macular Degeneration (nAMD). We developed three tools to analyze Optical Coherence Tomography Angiographโ€ฆ

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