Deep reinforcement learning: An overview
Y Li - arXiv preprint arXiv:1701.07274, 2017 - arxiv.org
We give an overview of recent exciting achievements of deep reinforcement learning (RL).
We discuss six core elements, six important mechanisms, and twelve applications. We start …
We discuss six core elements, six important mechanisms, and twelve applications. We start …
Deep reinforcement learning
SE Li - Reinforcement learning for sequential decision and …, 2023 - Springer
Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …
decision strategies. However, in many cases, it is desirable to learn directly from …
Deft: Dexterous fine-tuning for real-world hand policies
Dexterity is often seen as a cornerstone of complex manipulation. Humans are able to
perform a host of skills with their hands, from making food to operating tools. In this paper …
perform a host of skills with their hands, from making food to operating tools. In this paper …
Cobots and the benefits of their implementation in intelligent manufacturing
R Galin, R Meshcheryakov, S Kamesheva… - IOP conference …, 2020 - iopscience.iop.org
The perspective of robotics in intelligent manufacturing becomes with Industry 4.0.
Increasing the profitability of production is the main goal, which also depends on the …
Increasing the profitability of production is the main goal, which also depends on the …
Examining the role of safety in the low adoption rate of collaborative robots
Collaborative robots (cobots) are important accelerators of industrial growth. Their potential
is undisputed, yet cobot adoption remains low. Safety is one of the factors that influence …
is undisputed, yet cobot adoption remains low. Safety is one of the factors that influence …
Reinforcement Learning-based Approaches for Improving Safety and Trust in Robot-to-Robot and Human-Robot Interaction
M Abouelyazid - Advances in Urban Resilience and Sustainable …, 2024 - orientreview.com
The increasing deployment of robotic systems in various domains has emphasized the need
for ensuring safety and trust in robot-to-robot and human-robot interaction. Existing …
for ensuring safety and trust in robot-to-robot and human-robot interaction. Existing …
Prediction of human arm target for robot reaching movements
The raise of collaborative robotics has allowed to create new spaces where robots and
humans work in proximity. Consequently, to predict human movements and his/her final …
humans work in proximity. Consequently, to predict human movements and his/her final …
Augmented lagrangian method for instantaneously constrained reinforcement learning problems
In this paper, we study the Instantaneously Constrained Reinforcement Learning (ICRL)
problem, in which we are tasked to find a reward-maximizing policy while satisfying certain …
problem, in which we are tasked to find a reward-maximizing policy while satisfying certain …
Provable probabilistic safety and feasibility-assured control for autonomous vehicles using exponential control barrier functions
With the increasing need for safe control in the domain of autonomous driving, model-based
safety-critical control approaches are widely used, especially Control Barrier Function (CBF) …
safety-critical control approaches are widely used, especially Control Barrier Function (CBF) …
Distributing tasks in multi-agent robotic system for human-robot interaction applications
R Galin, R Meshcheryakov, S Kamesheva - International conference on …, 2020 - Springer
Human-robot interaction become a trend in robotics and happen in a wide range of
situations. This research paper describes human and collaborative robots interaction behind …
situations. This research paper describes human and collaborative robots interaction behind …