Deep reinforcement learning for robotics: A survey of real-world successes
Reinforcement learning (RL), particularly its combination with deep neural networks,
referred to as deep RL (DRL), has shown tremendous promise across a wide range of …
referred to as deep RL (DRL), has shown tremendous promise across a wide range of …
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 …
Multi-agent deep reinforcement learning: a survey
The advances in reinforcement learning have recorded sublime success in various domains.
Although the multi-agent domain has been overshadowed by its single-agent counterpart …
Although the multi-agent domain has been overshadowed by its single-agent counterpart …
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 …
Human motion trajectory prediction: A survey
With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …
of such systems to perceive, understand, and anticipate human behavior becomes …
Automated guided vehicle systems, state-of-the-art control algorithms and techniques
Automated guided vehicles (AGVs) form a large and important part of the logistic transport
systems in today's industry. They are used on a large scale, especially in Europe, for over a …
systems in today's industry. They are used on a large scale, especially in Europe, for over a …
A review of cooperative multi-agent deep reinforcement learning
Abstract Deep Reinforcement Learning has made significant progress in multi-agent
systems in recent years. The aim of this review article is to provide an overview of recent …
systems in recent years. The aim of this review article is to provide an overview of recent …
Core challenges of social robot navigation: A survey
Robot navigation in crowded public spaces is a complex task that requires addressing a
variety of engineering and human factors challenges. These challenges have motivated a …
variety of engineering and human factors challenges. These challenges have motivated a …