Results 171 to 180 of about 533,555 (259)
Advances in Difference-in-differences Methods for Policy Evaluation Research. [PDF]
Wang G, Hamad R, White JS.
europepmc +1 more source
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
Machine Learning Algorithms to Estimate Propensity Scores in Health Policy Evaluation: A Scoping Review. [PDF]
Lourenço L +4 more
europepmc +1 more source
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
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
Policy evaluation and optimization for photovoltaic poverty alleviation projects in Anhui Province of China. [PDF]
Xu S, Zhang Q, Yang L.
europepmc +1 more source
LLM‐Integrated Human–Robot Interaction System for Microrobots
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

