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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 reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution
AH Ganesh, B Xu - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The impact of internal combustion engine-powered automobiles on climate change due to
emissions and the depletion of fossil fuels has contributed to the progress of electrified …
emissions and the depletion of fossil fuels has contributed to the progress of electrified …
Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness
Driving safety is the most important element that needs to be considered for autonomous
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
Partially observable markov decision processes in robotics: A survey
Noisy sensing, imperfect control, and environment changes are defining characteristics of
many real-world robot tasks. The partially observable Markov decision process (POMDP) …
many real-world robot tasks. The partially observable Markov decision process (POMDP) …
Multi-agent deep reinforcement learning for multi-robot applications: A survey
J Orr, A Dutta - Sensors, 2023 - mdpi.com
Deep reinforcement learning has produced many success stories in recent years. Some
example fields in which these successes have taken place include mathematics, games …
example fields in which these successes have taken place include mathematics, games …
Voronoi-based multi-robot autonomous exploration in unknown environments via deep reinforcement learning
Autonomous exploration is an important application of multi-vehicle systems, where a team
of networked robots are coordinated to explore an unknown environment collaboratively …
of networked robots are coordinated to explore an unknown environment collaboratively …
Motion planning among dynamic, decision-making agents with deep reinforcement learning
Robots that navigate among pedestrians use collision avoidance algorithms to enable safe
and efficient operation. Recent works present deep reinforcement learning as a framework …
and efficient operation. Recent works present deep reinforcement learning as a framework …