Learning-based methods of perception and navigation for ground vehicles in unstructured environments: A review
DC Guastella, G Muscato - Sensors, 2020 - mdpi.com
The problem of autonomous navigation of a ground vehicle in unstructured environments is
both challenging and crucial for the deployment of this type of vehicle in real-world …
both challenging and crucial for the deployment of this type of vehicle in real-world …
Recent advances in artificial intelligence and tactical autonomy: Current status, challenges, and perspectives
This paper presents the findings of detailed and comprehensive technical literature aimed at
identifying the current and future research challenges of tactical autonomy. It discusses in …
identifying the current and future research challenges of tactical autonomy. It discusses in …
Deep federated learning for autonomous driving
Autonomous driving is an active research topic in both academia and industry. However,
most of the existing solutions focus on improving the accuracy by training learnable models …
most of the existing solutions focus on improving the accuracy by training learnable models …
Multiple meta-model quantifying for medical visual question answering
Transfer learning is an important step to extract meaningful features and overcome the data
limitation in the medical Visual Question Answering (VQA) task. However, most of the …
limitation in the medical Visual Question Answering (VQA) task. However, most of the …
Coarse-to-fine reasoning for visual question answering
Bridging the semantic gap between image and question is an important step to improve the
accuracy of the Visual Question Answering (VQA) task. However, most of the existing VQA …
accuracy of the Visual Question Answering (VQA) task. However, most of the existing VQA …
A sim-to-real pipeline for deep reinforcement learning for autonomous robot navigation in cluttered rough terrain
Robots that autonomously navigate real-world 3D cluttered environments need to safely
traverse terrain with abrupt changes in surface normals and elevations. In this letter, we …
traverse terrain with abrupt changes in surface normals and elevations. In this letter, we …
Terp: Reliable planning in uneven outdoor environments using deep reinforcement learning
K Weerakoon, AJ Sathyamoorthy… - … on Robotics and …, 2022 - ieeexplore.ieee.org
We present a novel method for reliable robot navigation in uneven outdoor terrains. Our
approach employs a fully-trained Deep Reinforcement Learning (DRL) network that uses …
approach employs a fully-trained Deep Reinforcement Learning (DRL) network that uses …
Proactive anomaly detection for robot navigation with multi-sensor fusion
Despite the rapid advancement of navigation algorithms, mobile robots often produce
anomalous behaviors that can lead to navigation failures. The ability to detect such …
anomalous behaviors that can lead to navigation failures. The ability to detect such …
[PDF][PDF] A Survey on Terrain Traversability Analysis for Autonomous Ground Vehicles: Methods, Sensors, and Challenges.
Understanding the terrain in the upcoming path of a ground robot is one of the most
challenging problems in field robotics. Terrain and traversability analysis is a …
challenging problems in field robotics. Terrain and traversability analysis is a …
Graph-based person signature for person re-identifications
The task of person re-identification (ReID) is to match images of the same person over
multiple non-overlapping camera views. Due to the variations in visual factors, previous …
multiple non-overlapping camera views. Due to the variations in visual factors, previous …