Safe deep reinforcement learning

Results 101 to 110 of about 9,252,589 (289)

Accelerating Optimal Building Control Through Reinforcement Learning with Surrogate Building Models

Applied Sciences
Buildings account for a substantial share of global energy use, yet the adoption of advanced optimal control strategies remains limited due to high computational costs and the difficulty of safe deployment.
Andres Sebastian Cespedes Cubides +2 more
doaj +1 more source

Hybrid Continuum Robot Designs and Architectures for Healthcare Applications

Advanced Robotics Research, EarlyView.
Hybrid continuum robots represent an emerging class of flexible manipulators that blend materials, structures, and actuation concepts from the established fields of soft and continuum robotics. This review introduces an accessible framework to distinguish key hybridization approaches, surveys current designs aimed at complex clinical applications, and ...
Burak Ozdemir +4 more
wiley +1 more source

BIT*+TD3 Hybrid Algorithm for Energy-Efficient Path Planning of Unmanned Surface Vehicles in Complex Inland Waterways

Applied Sciences
This research proposes a hybrid path planning framework for intelligent inland waterway Unmanned Surface Vehicles (USVs), which integrates the enhanced BIT* (Batch Informed Trees) algorithm with the TD3 (Twin Delayed Deep Deterministic Policy Gradient ...
Yunze Xie +4 more
doaj +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley +1 more source

Optimal distributed energy systems scheduling using a feasibility consistent safe deep reinforcement learning mechanism

Measurement: Energy
Driven by global decarbonization targets, the increasing penetration of distributed renewable energy has significantly increased the complexity of real-time scheduling in distributed energy systems (DES).
Yuanbo Shi +6 more
doaj +1 more source

Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots

Advanced Robotics Research, EarlyView.
This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou +4 more
wiley +1 more source

Enhancing Autonomous Driving in Urban Scenarios: A Hybrid Approach with Reinforcement Learning and Classical Control

Sensors
The use of Deep Learning algorithms in the domain of Decision Making for Autonomous Vehicles has garnered significant attention in the literature in recent years, showcasing considerable potential.
Rodrigo Gutiérrez-Moreno +5 more
doaj +1 more source

Disentangling Uncertainty for Safe Social Navigation using Deep Reinforcement Learning

2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Accepted at 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 8 pages, 6 figures and 4 ...
Daniel Flögel +3 more
openaire +3 more sources

Mutual Adaptation and Influence: Review of Latent Dynamics Models in Human–Robot Interaction

Advanced Robotics Research, EarlyView.
Robots are becoming better teammates by learning hidden patterns in how people act. This review covers how state‐of‐the‐art approaches leverage these patterns to help robots not only react but also anticipate and guide cooperation. Here, we synthesize a unifying framework for these approaches, classify and review existing works, and highlight key ...
Mason O. Smith +4 more
wiley +1 more source

Intrusion Detection and Prevention System (IDPS) Model for IIoT Environments Using Hybridized Framework

IEEE Access
As the Industrial Internet of Things (IIoT) becomes more popular, cyber threats have more places to attack. This is why intrusion detection and prevention systems (IDPS) are so important for keeping industrial environments safe and secure.
Manohar Srinivasan, N. C. Senthilkumar
doaj +1 more source

deep reinforcement learning
reinforcement learning
autonomous driving

path planning
adaptive cruise control
safe reinforcement learning

constrained markov decision process