Results 121 to 130 of about 7,404,725 (288)

A prioritized soft actor-critic algorithm for safe and efficient power distribution network reconfiguration

Frontiers in Energy Research
IntroductionDynamic network reconfiguration is a critical tool for enhancing the operational efficiency and security of power distribution networks. However, traditional model-based optimization methods are often computationally intensive and rely on ...
Ke Li, Qian Guo, Lizhou Jiang, JunHong Guo, Mengfan Min, Xuanang Gui, Yuheng Cheng, Junhua Zhao   +7 more
doaj   +1 more source

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

Advanced Robotics Research, EarlyView.
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang, Ganesh Arivoli, Huzaifa Unjhawala, Luning Bakke, Radu Serban, Dan Negrut   +5 more
wiley   +1 more source

SECRM‐2D: RL‐Based Efficient and Comfortable Route‐Following Autonomous Driving With Analytic Safety Guarantees

IET Intelligent Transport Systems
Over the last decade, there has been increasing interest in autonomous driving systems. Reinforcement learning (RL) shows great promise for training autonomous driving controllers, being able to directly optimize a combination of criteria such as ...
Tianyu Shi, Ilia Smirnov, Omar ElSamadisy, Baher Abdulhai   +3 more
doaj   +1 more source

Vehicle Lateral Control Based on Augmented Lagrangian DDPG Algorithm

Applied Sciences
This paper studies the safe trajectory tracking control of intelligent vehicles, which is still an open and challenging problem. A deep reinforcement learning algorithm based on augmented Lagrangian safety constraints is proposed to the lateral control ...
Zhi Li, Meng Wang, Haitao Zhao
doaj   +1 more source

Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling

Advanced Robotics Research, EarlyView.
This article introduces textile‐based pneumatic grippers that transform simple textiles into robust bending actuators. Detailed experiments uncover how cut geometry and fabric selection shape performance. Successful handling of fragile agricultural items showcases the potential of textile robotics for safe, scalable automation in food processing and ...
Zeyu Hou, Eran Beeri Bamani, Joao Buzzatto, Bryan Busby, Lucas Ferrari Gerez   +4 more
wiley   +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, Zhiqiang Chen, Yuanbiao Ma, Zhiqiang Tang, Qianqian Wang   +4 more
wiley   +1 more source

Safe Reinforcement Learning for Arm Manipulation with Constrained Markov Decision Process

Robotics
In the world of human–robot coexistence, ensuring safe interactions is crucial. Traditional logic-based methods often lack the intuition required for robots, particularly in complex environments where these methods fail to account for all possible ...
Patrick Adjei, Norman Tasfi, Santiago Gomez-Rosero, Miriam A. M. Capretz   +3 more
doaj   +1 more source

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, Sunny Amatya, Seyed Yousef Soltanian, Jonathan Bush, Wenlong Zhang   +4 more
wiley   +1 more source

DRIVE‐SAFE: Data‐Driven Robustness and Informed Validation for Evolving Specifications via Formal Evaluation

Advanced Robotics Research, EarlyView.
DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano, Jianyu An, Dinesh Manocha, Huan Xu   +3 more
wiley   +1 more source

Feasibility Consistent Representation Learning for Safe Reinforcement Learning

CoRR
In the field of safe reinforcement learning (RL), finding a balance between satisfying safety constraints and optimizing reward performance presents a significant challenge. A key obstacle in this endeavor is the estimation of safety constraints, which is typically more difficult than estimating a reward metric due to the sparse nature of the ...
Zhepeng Cen, Yihang Yao, Zuxin Liu, Ding Zhao   +3 more
openaire   +3 more sources