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Multi-IMU Proprioceptive Odometry for Legged Robots

IEEE/RJS International Conference on Intelligent RObots and Systems, 2023
This paper presents a novel, low-cost proprioceptive sensing solution for legged robots with point feet to achieve accurate low-drift long-term position and velocity estimation. In addition to conventional sensors, including one body Inertial Measurement
Shuo Yang   +3 more
semanticscholar   +1 more source

A Factor Graph Optimization Method for High-Precision IMU-Based Navigation System

IEEE Transactions on Instrumentation and Measurement, 2023
Multisensor-integrated navigation systems based on factor graph are increasingly used on indoor robots, UAVs, and other vehicles. The output information of the equipped low-cost inertial measurement unit (IMU) is usually processed by IMU preintegration ...
Pin Lyu   +5 more
semanticscholar   +1 more source

IMUNet: Efficient Regression Architecture for Inertial IMU Navigation and Positioning

IEEE Transactions on Instrumentation and Measurement
Data-driven method for inertial navigation and positioning has absorbed attention in recent years and it outperforms all its competitor methods in terms of accuracy and efficiency. This article introduces a new neural architecture framework called IMUNet
Behnam Zeinali   +2 more
semanticscholar   +1 more source

IMU Hand Calibration for Low-Cost MEMS Inertial Sensors

IEEE Transactions on Instrumentation and Measurement, 2023
This article proposes a technique to calibrate a low-cost inertial measurement unit (IMU) in the field without relying on expensive laboratory-based equipment.
Hussein Al Jlailaty   +3 more
semanticscholar   +1 more source

GLIO: Tightly-Coupled GNSS/LiDAR/IMU Integration for Continuous and Drift-Free State Estimation of Intelligent Vehicles in Urban Areas

IEEE Transactions on Intelligent Vehicles
Intelligent vehicles demand reliable, continuous, and accurate positioning capability. Light Detection and Ranging (LiDAR)-inertial odometry (LIO) provides precise continuous relative pose estimation but suffers from drift over large-scale operations ...
Xi-Kun Liu, W. Wen, Li-Ta Hsu
semanticscholar   +1 more source

Masked Video and Body-worn IMU Autoencoder for Egocentric Action Recognition

European Conference on Computer Vision
Compared with visual signals, Inertial Measurement Units (IMUs) placed on human limbs can capture accurate motion signals while being robust to lighting variation and occlusion.
Mingfang Zhang   +3 more
semanticscholar   +1 more source

Two-Step LiDAR/Camera/IMU Spatial and Temporal Calibration Based on Continuous-Time Trajectory Estimation

IEEE transactions on industrial electronics (1982. Print)
Accurate intersensor spatiotemporal transformation is the fundamental prerequisite for multisensor fusion. However, traditional discrete-time calibration methods have natural shortcomings when dealing with distorted and asynchronous raw measurements ...
Shengyu Li   +4 more
semanticscholar   +1 more source

Combining IMU With Acoustics for Head Motion Tracking Leveraging Wireless Earphone

IEEE Transactions on Mobile Computing
Head motion tracking is a promising research field with vast applications in ubiquitous human-computer interaction (HCI) scenarios. Unfortunately, solutions based on vision and wireless sensing have shortcomings in user privacy and tracking range ...
Jingyang Hu   +6 more
semanticscholar   +1 more source

Observability-Aware Intrinsic and Extrinsic Calibration of LiDAR-IMU Systems

IEEE Transactions on robotics, 2022
Accurate and reliable sensor calibration is essential to fuse LiDAR and inertial measurements, which are usually available in robotic applications.
Jiajun Lv   +5 more
semanticscholar   +1 more source

GPS-IMU Sensor Fusion for Reliable Autonomous Vehicle Position Estimation

arXiv.org
Global Positioning System (GPS) navigation provides accurate positioning with global coverage, making it a reliable option in open areas with unobstructed sky views. However, signal degradation may occur in indoor spaces and urban canyons.
S. Y. Alaba
semanticscholar   +1 more source

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