ArticleSensors (Basel, Switzerland)2025
AI-Driven Dynamic Covariance for ROS 2 Mobile Robot Localization.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A High-Precision Odometry Calibration Method for Mecanum-Wheeled Mobile Robots Based on ZUPT and Closed-Loop Pose Estimation.Sensors (Basel, Switzerland) · 2026Article
- Lightweight Semantic-Aware Route Planning on Edge Hardware for Indoor Mobile Robots: Monocular Camera-2D LiDAR Fusion with Penalty-Weighted Nav2 Route Server Replanning.Sensors (Basel, Switzerland) · 2026Article
- ROS-Based Navigation and Obstacle Avoidance: A Study of Architectures, Methods, and Trends.Sensors (Basel, Switzerland) · 2025Review
- Comparison of Two System Identification Approaches for a Four-Wheel Differential Robot Based on Velocity Command Execution.Sensors (Basel, Switzerland) · 2025Article
- ATRON: Autonomous trash retrieval for oceanic neatness.Frontiers in robotics and AI · 2025Article
Corrections and comments
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Authors and funding
1 author.
Funding
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Abstract
In the evolving field of mobile robotics, enhancing localization robustness in dynamic environments remains a critical challenge, particularly for ROS 2-based systems where sensor fusion plays a pivotal role. This study evaluates an AI-driven approach to dynamically adjust covariance parameters for improved pose estimation in a differential-drive mobile robot. A regression model was integrated into the
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.