Results 151 to 160 of about 5,734,703 (295)

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

Advanced 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, Amirreza Davar, Dongyi Wang   +2 more
wiley   +1 more source

Reflections on the Stability and Growth Pact’s Preventive Arm in Light of the COVID-19 Crisis

Intereconomics, 2020
Sebastian Hauptmeier, Nadine Leiner-Killinger   +1 more
doaj   +1 more source

Awareness, Experiences, and Attitudes Toward Preprints Among Medical Academics: Convergent Mixed Methods Study. [PDF]

JMIRx Med
Sevim M, Karamese B, Alparslan Z.
europepmc   +1 more source

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

Advanced 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, Zhengtong Xu, Siavash Mahmoudi, Pouya Sohrabipour, Chaitanya Pallerla, Yu She, Wan Shou, Philip Glen Crandall, Dongyi Wang   +8 more
wiley   +1 more source

Policy mix for a low-carbon food system. [PDF]

Front Nutr
Buso M, Banerjee S, West TAP.
europepmc   +1 more source

Education Policy is Health Policy

INQUIRY: The Journal of Health Care Organization, Provision, and Financing, 2007
openaire   +3 more sources

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

Advanced 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, Hongzhou Ai, Wenjun Xu, Zude Zhou, Lihui Wang   +4 more
wiley   +1 more source

Trends in ethnic disparities in reproductive, maternal, neonatal and child health interventions and the role of social investment and inclusive policies: a mixed-methods study in Ecuador, 2004-2018. [PDF]

BMJ Open
Rios-Quituizaca P, Endara-Mina J, Ferreira LZ, Armenta-Paulino N.   +3 more
europepmc   +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

Understanding policy alignment in addressing hydrological hazards in the Niger Delta region, Nigeria. [PDF]

PLoS One
Agumagu OO, Marchant R, Stringer LC.
europepmc   +1 more source