Zobrazeno 1 - 10
of 2 373
pro vyhledávání: '"Xie, Lihua"'
In this paper, we present an efficient visual SLAM system designed to tackle both short-term and long-term illumination challenges. Our system adopts a hybrid approach that combines deep learning techniques for feature detection and matching with tra
Externí odkaz:
http://arxiv.org/abs/2408.03520
For most existing prescribed performance formation control methods, performance requirements are not directly imposed on the relative states between agents but on the consensus error, which lacks a clear physical interpretation of their solution. In
Externí odkaz:
http://arxiv.org/abs/2408.00323
A differential dynamic programming (DDP)-based framework for inverse reinforcement learning (IRL) is introduced to recover the parameters in the cost function, system dynamics, and constraints from demonstrations. Different from existing work, where
Externí odkaz:
http://arxiv.org/abs/2407.19902
High-precision control for nonlinear systems is impeded by the low-fidelity dynamical model and external disturbance. Especially, the intricate coupling between internal uncertainty and external disturbance is usually difficult to be modeled explicit
Externí odkaz:
http://arxiv.org/abs/2407.13229
There is a significant demand for indoor localization technology in smart buildings, and the most promising solution in this field is using RF sensors and fingerprinting-based methods that employ machine learning models trained on crowd-sourced user
Externí odkaz:
http://arxiv.org/abs/2407.07921
Autor:
Yu, Wenlu, Xu, Jie, Zhao, Chengwei, Zhao, Lijun, Nguyen, Thien-Minh, Yuan, Shenghai, Bai, Mingming, Xie, Lihua
LiDAR odometry is a pivotal technology in the fields of autonomous driving and autonomous mobile robotics. However, most of the current works focus on nonlinear optimization methods, and still existing many challenges in using the traditional Iterati
Externí odkaz:
http://arxiv.org/abs/2407.02190
This paper considers the collaborative graph exploration problem in GPS-denied environments, where a group of robots are required to cover a graph environment while maintaining reliable pose estimations in collaborative simultaneous localization and
Externí odkaz:
http://arxiv.org/abs/2407.01013
Visual Odometry (VO) is vital for the navigation of autonomous systems, providing accurate position and orientation estimates at reasonable costs. While traditional VO methods excel in some conditions, they struggle with challenges like variable ligh
Externí odkaz:
http://arxiv.org/abs/2404.04677
Publikováno v:
ECCV 2024
Human pose estimation (HPE) from Radio Frequency vision (RF-vision) performs human sensing using RF signals that penetrate obstacles without revealing privacy (e.g., facial information). Recently, mmWave radar has emerged as a promising RF-vision sen
Externí odkaz:
http://arxiv.org/abs/2403.16198
Inspired by the behavior of birds, we present AirCrab, a hybrid aerial ground manipulator (HAGM) with a single active wheel and a 3-degree of freedom (3-DoF) manipulator. AirCrab leverages a single point of contact with the ground to reduce position
Externí odkaz:
http://arxiv.org/abs/2403.15805