Results 131 to 140 of about 6,760,003 (255)

A State‐Adaptive Koopman Control Framework for Real‐Time Deformable Tool Manipulation in Robotic Environmental Swabbing

open access: yesAdvanced Robotics Research, EarlyView.
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi   +2 more
wiley   +1 more source

ROMANIA'S POST-EU ACCESSION STATE AID POLICY [PDF]

open access: yesAnalele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie
This study examines the Romania's state aid policy after the country joined the European Union (EU) in 2007. With its membership, Romania's economic and regulatory environment underwent a dramatic change, bringing its policies into compliance with EU
MARIUS GEORGE POPA
doaj  

Between Different National Preferences and Conflicting Policy Objectives: The Difficulties in Establishing a Common European Energy Policy

open access: yesContemporary European Politics
In view of Russia's invasion of Ukraine and the global climate emergency, a strengthening of the common energy policy of the European Union (EU) seems more urgent than ever.
Lucas Schramm
doaj   +1 more source

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

open access: yesAdvanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar   +8 more
wiley   +1 more source

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

open access: yesAdvanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao   +4 more
wiley   +1 more source

Efficient and Robust Standing Postures of Quadruped Robots

open access: yesAdvanced Robotics Research, EarlyView.
A calibrated static framework estimates load, optimizes torques, and adapts posture so quadruped robots stand efficiently and robustly under external payloads, achieving up to 50% lower torque demand. Inspired by the natural posture adjustments of animals under external loading, this article presents an optimization‐based framework for minimizing joint
Mohamad Kanaan   +5 more
wiley   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

open access: yesAdvanced 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

A Critical Review of the Common Fisheries Policy [PDF]

open access: yes
The paper embodies an evaluation of the fishery policy at EU level. The common fishery policy is designed to solve a complex set of problems that emerge in the sector.
Carsten Lynge Jensen
core  

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

open access: yesAdvanced 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   +5 more
wiley   +1 more source

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