Review of autonomous path planning algorithms for mobile robots
H Qin, S Shao, T Wang, X Yu, Y Jiang, Z Cao - Drones, 2023 - mdpi.com
Mobile robots, including ground robots, underwater robots, and unmanned aerial vehicles,
play an increasingly important role in people's work and lives. Path planning and obstacle …
play an increasingly important role in people's work and lives. Path planning and obstacle …
A comprehensive review of recent research trends on unmanned aerial vehicles (uavs)
The growing interest in unmanned aerial vehicles (UAVs) from both the scientific and
industrial sectors has attracted a wave of new researchers and substantial investments in …
industrial sectors has attracted a wave of new researchers and substantial investments in …
HVIOnet: A deep learning based hybrid visual–inertial odometry approach for unmanned aerial system position estimation
Sensor fusion is used to solve the localization problem in autonomous mobile robotics
applications by integrating complementary data acquired from various sensors. In this study …
applications by integrating complementary data acquired from various sensors. In this study …
Robust adversarial attacks detection based on explainable deep reinforcement learning for uav guidance and planning
T Hickling, N Aouf, P Spencer - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
The dangers of adversarial attacks on Uncrewed Aerial Vehicle (UAV) agents operating in
public are increasing. Adopting AI-based techniques and, more specifically, Deep Learning …
public are increasing. Adopting AI-based techniques and, more specifically, Deep Learning …
Fiber reinforced composite manufacturing with the aid of artificial intelligence–a state-of-the-art review
Manufacturing of fiber reinforced polymer matrix composite materials is being done with
various methods in recent days. But controlling the accuracy of manufacturing and begetting …
various methods in recent days. But controlling the accuracy of manufacturing and begetting …
RGSO-UAV: Reverse Glowworm Swarm Optimization inspired UAV path-planning in a 3D dynamic environment
A Chowdhury, D De - Ad Hoc Networks, 2023 - Elsevier
Three-dimensional path planning for UAVs is a very complex, NP-hard optimization
problem. It is an effort to resolve the best feasible trajectory between the source and the …
problem. It is an effort to resolve the best feasible trajectory between the source and the …
Explainability in reinforcement learning: perspective and position
Artificial intelligence (AI) has been embedded into many aspects of people's daily lives and it
has become normal for people to have AI make decisions for them. Reinforcement learning …
has become normal for people to have AI make decisions for them. Reinforcement learning …
Federated explainable artificial intelligence (fXAI): a digital manufacturing perspective
A Kusiak - International Journal of Production Research, 2024 - Taylor & Francis
The industry has embraced digitalisation leading to a greater reliance on models derived
from data. Understanding and getting insights into the models generated by machine …
from data. Understanding and getting insights into the models generated by machine …
Explainability in deep reinforcement learning: A review into current methods and applications
T Hickling, A Zenati, N Aouf, P Spencer - ACM Computing Surveys, 2023 - dl.acm.org
The use of Deep Reinforcement Learning (DRL) schemes has increased dramatically since
their first introduction in 2015. Though uses in many different applications are being found …
their first introduction in 2015. Though uses in many different applications are being found …
A systematic literature review of flying ad hoc networks: State‐of‐the‐art, challenges, and perspectives
Unmanned aerial vehicles (UAVs), also known as drones, communicate, collaborate, and
form flying ad hoc networks (FANETs) to perform many different missions, ranging from …
form flying ad hoc networks (FANETs) to perform many different missions, ranging from …