Sim-to-real transfer in deep reinforcement learning for robotics: a survey
Deep reinforcement learning has recently seen huge success across multiple areas in the
robotics domain. Owing to the limitations of gathering real-world data, ie, sample inefficiency …
robotics domain. Owing to the limitations of gathering real-world data, ie, sample inefficiency …
Multi-agent deep reinforcement learning for multi-robot applications: A survey
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 …
Reinforcement learning for robot research: A comprehensive review and open issues
T Zhang, H Mo - International Journal of Advanced Robotic …, 2021 - journals.sagepub.com
Applying the learning mechanism of natural living beings to endow intelligent robots with
humanoid perception and decision-making wisdom becomes an important force to promote …
humanoid perception and decision-making wisdom becomes an important force to promote …
Federated learning in robotic and autonomous systems
Autonomous systems are becoming inherently ubiquitous with the advancements of
computing and communication solutions enabling low-latency offloading and real-time …
computing and communication solutions enabling low-latency offloading and real-time …
Self-improving situation awareness for human–robot-collaboration using intelligent Digital Twin
The situation awareness, especially for collaborative robots, plays a crucial role when
humans and machines work together in a human-centered, dynamic environment. Only …
humans and machines work together in a human-centered, dynamic environment. Only …
Position control of a mobile robot through deep reinforcement learning
This article proposes the use of reinforcement learning (RL) algorithms to control the
position of a simulated Kephera IV mobile robot in a virtual environment. The simulated …
position of a simulated Kephera IV mobile robot in a virtual environment. The simulated …
Self-improving models for the intelligent digital twin: Towards closing the reality-to-simulation gap
This paper presents a novel approach to ensure the quality of the Digital Twin models that
modern Cyber-Physical Manufacturing Systems (CPMS) rely on. CPMS are configurable …
modern Cyber-Physical Manufacturing Systems (CPMS) rely on. CPMS are configurable …
Towards Scalable Coverage-Based Testing of Autonomous Vehicles
To deploy autonomous vehicles (AVs) in the real world, developers must understand the
conditions in which the system can operate safely. To do this in a scalable manner, AVs are …
conditions in which the system can operate safely. To do this in a scalable manner, AVs are …
Towards lifelong federated learning in autonomous mobile robots with continuous sim-to-real transfer
The role of deep learning (DL) in robotics has significantly deepened over the last decade.
Intelligent robotic systems today are highly connected systems that rely on DL for a variety of …
Intelligent robotic systems today are highly connected systems that rely on DL for a variety of …
[كتاب][B] Machine learning safety
This book addresses the safety and security perspective of machine learning, focusing on its
vulnerability to environmental noise and various safety and security attacks. Machine …
vulnerability to environmental noise and various safety and security attacks. Machine …