Zobrazeno 1 - 10
of 690
pro vyhledávání: '"Liu, Ziyuan"'
Autor:
Liu, Puze, Günster, Jonas, Funk, Niklas, Gröger, Simon, Chen, Dong, Bou-Ammar, Haitham, Jankowski, Julius, Marić, Ante, Calinon, Sylvain, Orsula, Andrej, Olivares-Mendez, Miguel, Zhou, Hongyi, Lioutikov, Rudolf, Neumann, Gerhard, Zhalehmehrabi, Amarildo Likmeta Amirhossein, Bonenfant, Thomas, Restelli, Marcello, Tateo, Davide, Liu, Ziyuan, Peters, Jan
Machine learning methods have a groundbreaking impact in many application domains, but their application on real robotic platforms is still limited. Despite the many challenges associated with combining machine learning technology with robotics, robo
Externí odkaz:
http://arxiv.org/abs/2411.05718
The nonlinear damping characteristics of the oscillating wave surge converter (OWSC) significantly impact the performance of the power take-off system. This study presents a framework by integrating deep reinforcement learning (DRL) with numerical si
Externí odkaz:
http://arxiv.org/abs/2410.08871
To overcome these obstacles and improve computational accuracy and efficiency, this paper presents the Randomized Radial Basis Function Neural Network (RRNN), an innovative approach explicitly crafted for solving multiscale elliptic equations. The RR
Externí odkaz:
http://arxiv.org/abs/2407.14745
In this paper, we present a novel, scalable approach for constructing open set, instance-level 3D scene representations, advancing open world understanding of 3D environments. Existing methods require pre-constructed 3D scenes and face scalability is
Externí odkaz:
http://arxiv.org/abs/2407.14279
To enhance the robustness of the Light Gradient Boosting Machine (LightGBM) algorithm for image classification, a topological data analysis (TDA)-based robustness optimization algorithm for LightGBM, TDA-LightGBM, is proposed to address the interfere
Externí odkaz:
http://arxiv.org/abs/2406.13300
Autor:
Jia, Peijin, Wen, Tuopu, Luo, Ziang, Yang, Mengmeng, Jiang, Kun, Lei, Zhiquan, Tang, Xuewei, Liu, Ziyuan, Cui, Le, Zhang, Bo, Huang, Long, Yang, Diange
Constructing high-definition (HD) maps is a crucial requirement for enabling autonomous driving. In recent years, several map segmentation algorithms have been developed to address this need, leveraging advancements in Bird's-Eye View (BEV) perceptio
Externí odkaz:
http://arxiv.org/abs/2405.02008
Data generation is recognized as a potent strategy for unsupervised domain adaptation (UDA) pertaining semantic segmentation in adverse weathers. Nevertheless, these adverse weather scenarios encompass multiple possibilities, and high-fidelity data s
Externí odkaz:
http://arxiv.org/abs/2402.06446
Neural operators have been validated as promising deep surrogate models for solving partial differential equations (PDEs). Despite the critical role of boundary conditions in PDEs, however, only a limited number of neural operators robustly enforce t
Externí odkaz:
http://arxiv.org/abs/2312.06980
Publikováno v:
IEEE Robotics and Automation Letters, vol. 9, no. 2, pp. 955-962, Feb. 2024
Global visual localization estimates the absolute pose of a camera using a single image, in a previously mapped area. Obtaining the pose from a single image enables many robotics and augmented/virtual reality applications. Inspired by latest advances
Externí odkaz:
http://arxiv.org/abs/2312.02029
Publikováno v:
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Detroit, MI, USA, 2023, pp. 3358-3365
Re-localizing a camera from a single image in a previously mapped area is vital for many computer vision applications in robotics and augmented/virtual reality. In this work, we address the problem of estimating the 6 DoF camera pose relative to a gl
Externí odkaz:
http://arxiv.org/abs/2312.00500