Results 51 to 60 of about 6,304,901 (198)

Bi-level optimization-based scalable unmanned maritime search and rescue

工程科学学报
Owing to their advantages of low cost, high mobility, and convenient deployment, unmanned aerial vehicles (UAV) are increasingly being used for multiple tasks that require rapid responses, automatic handling, or collaborative operations.
Sen WANG, Shizhen WANG, Ningning LÜ, Youbo JING   +3 more
doaj   +1 more source

Hexapod Locomotion Across Structured and Unstructured Terrains: A Data‐Driven Review of Modeling, Control, and Validation

Journal of Field Robotics, EarlyView.
ABSTRACT The design of a hexapod is complex and requires integration between kinematic models, control systems, and sensing. Existing literature has reviewed these sub‐systems in isolation. Since 2021, there has been no review of the field despite significant advancements in soft soil, lunar traversal, and artificial intelligence.
Akhil Rampersad, Bashan Naidoo
wiley   +1 more source

Proximal Policy Optimization (PPO)-Based Resource Allocation for Energy Harvesting Industrial Wireless Sensor

, 2023
Abstract For the purpose of overcoming the challenges of charging wireless sensors in the complicated industrial environment, researchers are concentrating more and more on sensor networks that can harvest energy.This paper looks at a wirelessly powered industrial sensor network where each sensor harvests energy from a specific radio frequency (
Rongzhen Li, Lei Xu, Chengming Tang, Ping Wang, Wanli Liu, Junjie Gu, Zhicheng Cai, Rui Jiang   +7 more
openaire   +1 more source

AI‐enabled bumpless transfer control strategy for legged robot with hybrid energy storage system

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Designing Hybrid energy storage system (HESS) for a legged robot is significant to improve the motion performance and energy efficiency of the robot. However, switching between the driving mode and regenerative braking mode in the HESS may generate a torque bump, which has brought significant challenges to the stability of the robot locomotion.
Zhiwu Huang, Zi Yu, Hui Peng, Zixuan Wang, Xiaokang Dai, Weirong Liu, Jing Wang   +6 more
wiley   +1 more source

Hybrid Proximal Policy Optimization—Wasserstein Generative Adversarial Network Framework for Hosting Capacity Optimization in Renewable-Integrated Power Systems

Energies
The rapid integration of distributed energy resources (DERs) such as photovoltaics (PV), wind turbines, and energy storage systems has transformed modern power systems, with hosting capacity optimization emerging as a critical challenge.
Jun Han, Chao Cai, Wenjie Pan, Hong Liu, Zhengyang Xu   +4 more
doaj   +1 more source

Exploring and Exploiting Conditioning of Reinforcement Learning Agents

IEEE Access, 2020
The outcome of Jacobian singular values regularization was studied for supervised learning problems. In supervised learning settings for linear and nonlinear networks, Jacobian regularization allows for faster learning.
Arip Asadulaev, Igor Kuznetsov, Gideon Stein, Andrey Filchenkov   +3 more
doaj   +1 more source

Optimisation or Learning? Appropriate Choice of Models and Methods for Sequential Decision‐Making in Power System Operation

Energy Internet, EarlyView.
ABSTRACT Power system operation is inherently a sequential decision‐making problem, traditionally addressed through optimisation models built upon high‐quality load forecasts. However, the rapid proliferation of renewable generation and price‐responsive demands, such as electric vehicles and merchant energy storage, has introduced multiple sources of ...
Wei Wei, Runze Liang
wiley   +1 more source

Research on Adaptive Irrigation Decision‐Making Method for the Entire Growth Cycle of Water Spinach Based on Reinforcement Learning

Food Frontiers
To address the issues of irrigation decisions in water spinach production being highly dependent on experience and struggling to cope with rainfall uncertainty and crop growth stage differences, this study proposes an environmentally enhanced proximal ...
Ruipeng Tang, Loy Chee Luen, Wei Sun, Narendra Kumar Aridas, Mohamad Sofian Abu Talip   +4 more
doaj   +1 more source

A Robust Strategy for UAV Autonomous Landing on a Moving Platform under Partial Observability

Drones
Landing a multi-rotor uncrewed aerial vehicle (UAV) on a moving target in the presence of partial observability, due to factors such as sensor failure or noise, represents an outstanding challenge that requires integrative techniques in robotics and ...
Godwyll Aikins, Sagar Jagtap, Kim-Doang Nguyen   +2 more
doaj   +1 more source

AM-PPO: (Advantage) Alpha-Modulation with Proximal Policy Optimization

CoRR
Proximal Policy Optimization (PPO) is a widely used reinforcement learning algorithm that heavily relies on accurate advantage estimates for stable and efficient training. However, raw advantage signals can exhibit significant variance, noise, and scale-related issues, impeding optimal learning performance.
openaire   +2 more sources