Introspection of dnn-based perception functions in automated driving systems: State-of-the-art and open research challenges
Automated driving systems (ADSs) aim to improve the safety, efficiency and comfort of future
vehicles. To achieve this, ADSs use sensors to collect raw data from their environment. This …
vehicles. To achieve this, ADSs use sensors to collect raw data from their environment. This …
Robot proficiency self-assessment using assumption-alignment tracking
While the design of autonomous robots often emphasizes developing proficient robots,
another important attribute of autonomous robot systems is their ability to evaluate their own …
another important attribute of autonomous robot systems is their ability to evaluate their own …
Reliable Monte Carlo localization for mobile robots
N Akai - Journal of Field Robotics, 2023 - Wiley Online Library
Reliability is a key factor for realizing safety guarantee of fully autonomous robot systems. In
this paper, we focus on reliability in mobile robot localization. Monte Carlo localization …
this paper, we focus on reliability in mobile robot localization. Monte Carlo localization …
Hybrid localization using model-and learning-based methods: Fusion of Monte Carlo and E2E localizations via importance sampling
This paper proposes a hybrid localization method that fuses Monte Carlo localization (MCL)
and convolutional neural network (CNN)-based end-to-end (E2E) localization. MCL is based …
and convolutional neural network (CNN)-based end-to-end (E2E) localization. MCL is based …
Detection of localization failures using Markov random fields with fully connected latent variables for safe LiDAR-based automated driving
N Akai, Y Akagi, T Hirayama… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Most of the recent automated driving systems assume the accurate functioning of
localization. Unanticipated errors cause localization failures and result in failures in …
localization. Unanticipated errors cause localization failures and result in failures in …
Human face sketch to RGB image with edge optimization and generative adversarial networks
F Zhang, H Zhao, W Ying, Q Liu… - … Automation & Soft …, 2020 - scholarworks.utrgv.edu
Generating an RGB image from a sketch is a challenging and interesting topic. This paper
proposes a method to transform a face sketch into a color image based on generation …
proposes a method to transform a face sketch into a color image based on generation …
3D Monte Carlo localization with efficient distance field representation for automated driving in dynamic environments
This paper presents a LiDAR-based 3D Monte Carlo localization (MCL) with an efficient
distance field (DF) representation method. To implement 3D MCL, high computing capacity …
distance field (DF) representation method. To implement 3D MCL, high computing capacity …
Semantic localization considering uncertainty of object recognition
Semantics can be leveraged in ego-vehicle localization to improve robustness and accuracy
because objects with the same labels can be correctly matched with each other. Object …
because objects with the same labels can be correctly matched with each other. Object …
Mobile robot localization considering uncertainty of depth regression from camera images
N Akai - IEEE Robotics and Automation Letters, 2022 - ieeexplore.ieee.org
This letter presents a mobile robot localization method that uses depth regression from
camera images. In this work, we use convolutional neural networks to regress the depth from …
camera images. In this work, we use convolutional neural networks to regress the depth from …
A framework for collaborative multi-robot mapping using spectral graph wavelets
The exploration of large-scale unknown environments can benefit from the deployment of
multiple robots for collaborative mapping. Each robot explores a section of the environment …
multiple robots for collaborative mapping. Each robot explores a section of the environment …