Applications of artificial intelligence for disaster management
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …
socioeconomic loss. The actual damage and loss observed in the recent decades has …
Motion planning for mobile robots—Focusing on deep reinforcement learning: A systematic review
H Sun, W Zhang, R Yu, Y Zhang - IEEE Access, 2021 - ieeexplore.ieee.org
Mobile robots contributed significantly to the intelligent development of human society, and
the motion-planning policy is critical for mobile robots. This paper reviews the methods …
the motion-planning policy is critical for mobile robots. This paper reviews the methods …
Deep reinforcement learning robot for search and rescue applications: Exploration in unknown cluttered environments
Rescue robots can be used in urban search and rescue (USAR) applications to perform the
important task of exploring unknown cluttered environments. Due to the unpredictable …
important task of exploring unknown cluttered environments. Due to the unpredictable …
Edge technologies for disaster management: A survey of social media and artificial intelligence integration
Within the paradigm of smart cities, smart devices can be considered as a tool to enhance
safety. Edge sensing, Internet of Things (IoT), big data, social media analytics, edge …
safety. Edge sensing, Internet of Things (IoT), big data, social media analytics, edge …
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 …
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 …
Deep reinforcement learning for safe local planning of a ground vehicle in unknown rough terrain
S Josef, A Degani - IEEE Robotics and Automation Letters, 2020 - ieeexplore.ieee.org
Safe unmanned ground vehicle navigation in unknown rough terrain is crucial for various
tasks such as exploration, search and rescue and agriculture. Offline global planning is often …
tasks such as exploration, search and rescue and agriculture. Offline global planning is often …
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 …
A survey of traversability estimation for mobile robots
C Sevastopoulos, S Konstantopoulos - IEEE Access, 2022 - ieeexplore.ieee.org
Traversability illustrates the difficulty of driving through a specific region and encompasses
the suitability of the terrain for traverse based on its physical properties, such as slope and …
the suitability of the terrain for traverse based on its physical properties, such as slope and …
[HTML][HTML] A comprehensive survey of unmanned ground vehicle terrain traversability for unstructured environments and sensor technology insights
This article provides a detailed analysis of the assessment of unmanned ground vehicle
terrain traversability. The analysis is categorized into terrain classification, terrain mapping …
terrain traversability. The analysis is categorized into terrain classification, terrain mapping …