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Deep reinforcement learning based mobile robot navigation: A review
K Zhu, T Zhang - Tsinghua Science and Technology, 2021 - ieeexplore.ieee.org
Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement
Learning (DRL) has received significant attention because of its strong representation and …
Learning (DRL) has received significant attention because of its strong representation and …
A review of perception sensors, techniques, and hardware architectures for autonomous low-altitude UAVs in non-cooperative local obstacle avoidance
MZ Butt, N Nasir, RBA Rashid - Robotics and Autonomous Systems, 2024 - Elsevier
Abstract Unmanned Aerial Vehicles (UAVs) can detect and communicate with cooperative
obstacles through established protocols. However, non-cooperative obstacles pose a …
obstacles through established protocols. However, non-cooperative obstacles pose a …
Guidance and control of autonomous surface underwater vehicles for target tracking in ocean environment by deep reinforcement learning
This paper studies a guidance and control framework of multiple autonomous surface
underwater vehicles (multi-ASUV) based on deep reinforcement learning (DRL) for target …
underwater vehicles (multi-ASUV) based on deep reinforcement learning (DRL) for target …
Visuomotor reinforcement learning for multirobot cooperative navigation
This article investigates the multirobot cooperative navigation problem based on raw visual
observations. A fully end-to-end learning framework is presented, which leverages graph …
observations. A fully end-to-end learning framework is presented, which leverages graph …
Crowd-aware robot navigation for pedestrians with multiple collision avoidance strategies via map-based deep reinforcement learning
It is challenging for a mobile robot to navigate through human crowds. Existing approaches
usually assume that pedestrians follow a predefined collision avoidance strategy, like social …
usually assume that pedestrians follow a predefined collision avoidance strategy, like social …
Self-attention-based multi-agent continuous control method in cooperative environments
Cooperative problems under continuous control have always been the focus of multi-agent
reinforcement learning. Existing algorithms suffer from the problem of uneven learning …
reinforcement learning. Existing algorithms suffer from the problem of uneven learning …
Deep reinforcement learning in mobile robotics–a concise review
RG Prasuna, SR Potturu - Multimedia Tools and Applications, 2024 - Springer
Mobile robotics is one of the emerging research area in the robotics. The recently evolving
techniques, artificial intelligence and precise hardware controller design gave new scope in …
techniques, artificial intelligence and precise hardware controller design gave new scope in …
An intelligent path planning mechanism for firefighting in wireless sensor and actor networks
Forests have an important role in environmental preservation and maintenance. The primary
threat is forest fires, which have disastrous repercussions. As a result, it is critical to identify …
threat is forest fires, which have disastrous repercussions. As a result, it is critical to identify …
Learning to socially navigate in pedestrian-rich environments with interaction capacity
Existing navigation policies for autonomous robots tend to focus on collision avoidance
while ignoring human-robot interactions in social life. For instance, robots can pass along …
while ignoring human-robot interactions in social life. For instance, robots can pass along …
Pathrl: An end-to-end path generation method for collision avoidance via deep reinforcement learning
Robot navigation using deep reinforcement learning (DRL) has shown great potential in
improving the performance of mobile robots. Nevertheless, most existing DRL-based …
improving the performance of mobile robots. Nevertheless, most existing DRL-based …