Local path planning: Dynamic window approach with Q-learning considering congestion environments for mobile robot

M Kobayashi, H Zushi, T Nakamura, N Motoi - IEEE Access, 2023 - ieeexplore.ieee.org
In recent years, autonomous mobile robots have significantly increased in prevalence due to
their ability to augment and diversify the workforce. One critical aspect of their operation is …

[HTML][HTML] The Impact of LiDAR Configuration on Goal-Based Navigation within a Deep Reinforcement Learning Framework

KB Olayemi, M Van, S McLoone, S McIlvanna, Y Sun… - Sensors, 2023 - mdpi.com
Over the years, deep reinforcement learning (DRL) has shown great potential in mapless
autonomous robot navigation and path planning. These DRL methods rely on robots …

Explainable Gated Bayesian Recurrent Neural Network for Non-Markov State Estimation

S Yan, Y Liang, L Zheng, M Fan… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The optimality of Bayesian filtering relies on the completeness of prior models, while deep
learning holds a distinct advantage in learning models from offline data. Nevertheless, the …

Strong tracking square-root modified sliding-window variational adaptive Kalman filtering with unknown noise covariance matrices

S Qiao, Y Fan, G Wang, D Mu, Z He - Signal Processing, 2023 - Elsevier
The Kalman filter's performance deteriorates in the existence of slowly time-varying and
unknown measurement and process noise covariances. A simplified strong tracking square …

Asymptotically efficient estimator for range-based robot relative localization

Y Wang, M Lin, X Xie, Y Gao, F Deng… - … /ASME Transactions on …, 2023 - ieeexplore.ieee.org
This study investigates the 2-D relative localization problem, which estimates the relative
orientation and position between two moving robots using inter-robot range measurements …

Application of Ghost-DeblurGAN to fiducial marker detection

Y Liu, A Haridevan, H Schofield… - 2022 IEEE/RSJ …, 2022 - ieeexplore.ieee.org
Feature extraction or localization based on the fiducial marker could fail due to motion blur in
real-world robotic applications. To solve this problem, a lightweight generative adversarial …

Event‐triggered resilient joint mobile robot localization and sensor fault estimation

Y Lu, HR Karimi, B Li, CC Chen - International Journal of …, 2024 - Wiley Online Library
The event‐triggered joint sensor fault estimation and mobile robot (MR) localization (MRL)
problem (MRLP) subject to the potential fluctuations of the estimator gain are investigated …

Approximate Inference Particle Filtering for Mobile Robot SLAM

S Zhang, J Shan, Y Liu - IEEE Transactions on Automation …, 2024 - ieeexplore.ieee.org
This paper proposes approximate inference particle filtering for mobile robot simultaneous
localization and mapping (SLAM) with landmarks. Range-bearing measurements are …

Multi-level Gated Bayesian Recurrent Neural Network for State Estimation

S Yan, Y Liang, L Zheng, M Fan, B Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
The optimality of Bayesian filtering relies on the completeness of prior models, while deep
learning holds a distinct advantage in learning models from offline data. Nevertheless, the …

VB-T PHD-SLAM: efficient SLAM under heavy-tailed noise

H Zou, S Wu, Q Xue, X Sun, B Wang - Advanced Robotics, 2024 - Taylor & Francis
To address the challenge of simultaneous localization and mapping (SLAM) in the presence
of heavy-tailed noise, this paper introduces a robust probability hypothesis density (PHD) …