Results 131 to 140 of about 7,404,725 (288)

Concurrent Learning of Control Policy and Unknown Safety Specifications in Reinforcement Learning

IEEE Open Journal of Control Systems
Reinforcement learning (RL) has revolutionized decision-making across a wide range of domains over the past few decades. Yet, deploying RL policies in real-world scenarios presents the crucial challenge of ensuring safety.
Lunet Yifru, Ali Baheri
doaj   +1 more source

Intelligent Sky Guardians (InSkyGuard): An Aerial Robotic Swarm for Autonomous Detection and Entrapment of Rogue Multirotors

Advanced Robotics Research, EarlyView.
Intelligent Sky Guardians (InSkyGuard) is introduced as a four‐drone swarm that autonomously detects, tracks, and safely captures rogue drones using a coordinated net system. Computer vision and leader–follower control architecture enable synchronized enclosure, while integrated failsafes enhance system reliability. Validated through closed‐environment
Joshua Hastings, Levanya Dewanarayana, Iline Shaju, Haider Al‐Wizni, Sampson Marquis, Weicheng Huang, Pooya Sareh   +6 more
wiley   +1 more source

Chaos synchronization of two coupled map lattice systems using safe reinforcement learning

When synchronizing two continuous typical chaotic systems, the state variables of the response system are usually bounded and satisfy the Lipschitz condition. This permits a universal synchronization method. In the synchronization of two high-dimensional
Small, M., Ding, J., Jianfei Xie, Lei, Y.   +3 more
core   +1 more source

Implicit Safe Set Algorithm for Provably Safe Reinforcement Learning

Journal of Artificial Intelligence Research
Deep reinforcement learning (DRL) has demonstrated remarkable performance in many continuous control tasks. However, a significant obstacle to the real-world application of DRL is the lack of safety guarantees. Although DRL agents can satisfy system safety in expectation through reward shaping, designing agents to consistently meet hard constraints (e ...
Weiye Zhao, Feihan Li, Tairan He, Changliu Liu   +3 more
openaire   +2 more sources

AM-DIMPO: Action-Masked Diffusion-Implicit Policy Optimization for On-Ramp Merging Under Dense Traffic

Applied Sciences
Highway ramp merging requires autonomous vehicles to make safe and efficient decisions in dense mixed traffic, where strong vehicle interactions and rapidly changing acceptable gaps make the task particularly challenging.
Qiuqi Gao, Jiahong Li, Xiaoxiang Huang, Yidian Zhu, Yu Du   +4 more
doaj   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source

Scaling Reinforcement Learning Paradigms for Motor Control [PDF]

, 2003
Reinforcement learning offers a general framework to explain rewardrelated learning in artificial and biological motor control. However, current reinforcement learning methods rarely scale to high dimensional movement systems and mainly operate in ...
Vijayakumar, S.; id_orcid, Schaal, S., Peters, J.   +2 more
core  

Market-Aware and Topology-Embedded Safe Reinforcement Learning for Virtual Power Plant Dispatch

World Electric Vehicle Journal
To address the challenges faced by virtual power plants (VPPs) in uncertain market environments and complex distribution networks, including strong market coupling, difficulty in multi-resource coordination, and strict safety constraints, this paper ...
Yueping Xiang, Luoyi Li, Yanqiu Hou, Xiaoyu Dai, Wenfeng Peng, Zhuoyang Liu, Ziming Liu, Zicong Chen, Xingyu Hu, Lv He   +9 more
doaj   +1 more source

Continuum Robots in Surgery: From Engineering Design to Clinical Practice

Advanced Robotics Research, EarlyView.
The hyper‐redundant nature of continuum robot structures enables near‐infinite degrees of freedom leading to immense potential for medical applications. This review provides a historical background of continuum robots and novel ideas shaping their progress to current structural design, sensing technology, modeling techniques, and control methods.
Griffin Smith, Kaitlyn Clancy, Siwen Xie, Xiaochen Li, Sarah Khalife, Benjamin van der Woerd, Onaizah Onaizah   +6 more
wiley   +1 more source