中文
相关论文

相关论文: f2IMU-R: Pedestrian Navigation by Low-cost Foot-Mo…

200 篇论文

In this paper we propose a novel accurate method for dead-reckoning of wheeled vehicles based only on an Inertial Measurement Unit (IMU). In the context of intelligent vehicles, robust and accurate dead-reckoning based on the IMU may prove…

机器人学 · 计算机科学 2019-04-15 Martin Brossard , Axel Barrau , Silvère Bonnabel

Foot-mounted inertial positioning (FMIP) can face problems of inertial drifts and unknown initial states in real applications, which renders the estimated trajectories inaccurate and not obtained in a well defined coordinate system for…

机器学习 · 统计学 2017-06-05 Yang Gu , Caifa Zhou , Andreas Wieser , Zhimin Zhou

This paper addresses accurate pose estimation (position, velocity, and orientation) for a rigid body using a combination of generic inertial-frame and/or body-frame measurements along with an Inertial Measurement Unit (IMU). By embedding…

系统与控制 · 电气工程与系统科学 2025-04-08 Sifeddine Benahmed , Soulaimane Berkane , Tarek Hamel

Sparse wearable inertial measurement units (IMUs) have gained popularity for estimating 3D human motion. However, challenges such as pose ambiguity, data drift, and limited adaptability to diverse bodies persist. To address these issues, we…

The task of indoor positioning is fundamental to several applications, including navigation, healthcare, location-based services, and security. An emerging field is inertial navigation for pedestrians, which relies only on inertial sensors…

机器人学 · 计算机科学 2025-01-28 Itzik Klein

Baseline generation for tracking applications is a difficult task when working with real world radar data. Data sparsity usually only allows an indirect way of estimating the original tracks as most objects' centers are not represented in…

信号处理 · 电气工程与系统科学 2019-07-24 Nicolas Scheiner , Stefan Haag , Nils Appenrodt , Bharanidhar Duraisamy , Jürgen Dickmann , Martin Fritzsche , Bernhard Sick

Recent studies confirm the applicability of Inertial Measurement Unit (IMU)-based systems for human motion analysis. Notwithstanding, high-end IMU-based commercial solutions are yet too expensive and complex to democratize their use among a…

Inertial odometry (IO) using strap-down inertial measurement units (IMUs) is critical in many robotic applications where precise orientation and position tracking are essential. Prior kinematic motion model-based IO methods often use a…

机器人学 · 计算机科学 2024-05-16 Yuheng Qiu , Chen Wang , Can Xu , Yutian Chen , Xunfei Zhou , Youjie Xia , Sebastian Scherer

Environment awareness is crucial for enhancing walking safety and stability of amputee wearing powered prosthesis when crossing uneven terrains such as stairs and obstacles. However, existing environmental perception systems for prosthesis…

机器人学 · 计算机科学 2024-04-30 Chuheng Chen , Xinxing Chen , Shucong Yin , Yuxuan Wang , Binxin Huang , Yuquan Leng , Chenglong Fu

Inertial motion capture is a promising approach for capturing motion outside the laboratory. However, as one major drawback, most of the current methods require different quantities to be calibrated or computed offline as part of the setup…

机器人学 · 计算机科学 2025-09-17 Michael Lorenz , Bertram Taetz , Gabriele Bleser-Taetz , Didier Stricker

In this article, a tutorial introduction to visual-inertial navigation(VIN) is presented. Visual and inertial perception are two complementary sensing modalities. Cameras and inertial measurement units (IMU) are the corresponding sensors…

机器人学 · 计算机科学 2023-07-25 Yangyang Ning

Reliable odometry for legged robots without cameras or LiDAR remains challenging due to IMU drift and noisy joint velocity sensing. This paper presents a purely proprioceptive state estimator that uses only IMU and motor measurements to…

机器人学 · 计算机科学 2026-02-23 Minxing Sun , Yao Mao

This paper introduces a new approach to 3-D position estimation from acceleration data, i.e., a 3-D motion tracking system having a small size and low-cost magnetic and inertial measurement unit (MIMU) composed by both a digital compass and…

机器人学 · 计算机科学 2013-11-20 P. Neto , J. N. Pires , A. P Moreira

Different technologies can acquire data for gait analysis, such as optical systems and inertial measurement units (IMUs). Each technology has its drawbacks and advantages, fitting best to particular applications. The presented multi-sensor…

人机交互 · 计算机科学 2021-12-01 Geise Santos , Marcelo Wanderley , Tiago Tavares , Anderson Rocha

Estimating the limbs pose in a wearable way may benefit multiple areas such as rehabilitation, teleoperation, human-robot interaction, gaming, and many more. Several solutions are commercially available, but they are usually expensive or…

A pedestrian navigation system (PNS) in indoor environments, where global navigation satellite system (GNSS) signal access is difficult, is necessary, particularly for search and rescue (SAR) operations in large buildings. This paper…

信号处理 · 电气工程与系统科学 2024-02-27 Seunghyeon Park , Taewon Kang , Seungjae Lee , Joon Hyo Rhee

Accurate and continuous pedestrian positioning across outdoor-indoor environments remains challenging because GNSS, UWB, and inertial PDR are complementary yet individually fragile under signal blockage, multipath, and drift. This paper…

This paper presents a novel constrained Factor Graph Optimization (FGO)-based approach for networked inertial navigation in pedestrian localization. To effectively mitigate the drift inherent in inertial navigation solutions, we incorporate…

机器人学 · 计算机科学 2025-05-14 Yingjie Hu , Wang Hu

The miniaturization of inertial measurement units (IMUs) facilitates their widespread use in a growing number of application domains. Orientation estimation is a prerequisite for most further data processing steps in inertial motion…

系统与控制 · 电气工程与系统科学 2022-10-28 Daniel Laidig , Thomas Seel

An inertial navigation system (INS) utilizes three orthogonal accelerometers and gyroscopes to determine platform position, velocity, and orientation. There are countless applications for INS, including robotics, autonomous platforms, and…

信号处理 · 电气工程与系统科学 2024-03-26 Zeev Yampolsky , Yair Stolero , Nitzan Pri-Hadash , Dan Solodar , Shira Massas , Itai Savin , Itzik Klein