Results 111 to 120 of about 2,010,813 (260)

I-CTRL: Imitation to Control Humanoid Robots Through Constrained Reinforcement Learning [PDF]

open access: yesarXiv
Humanoid robots have the potential to mimic human motions with high visual fidelity, yet translating these motions into practical, physical execution remains a significant challenge. Existing techniques in the graphics community often prioritize visual fidelity over physics-based feasibility, posing a significant challenge for deploying bipedal systems
arxiv  

Identifying physics misconceptions at the circus: The case of circular motion [PDF]

open access: gold, 2020
Alexander Volfson   +2 more
openalex   +1 more source

Pre-Service Physics Teachers’ Problem-solving Skills in Projectile Motion Concept [PDF]

open access: gold, 2017
Sutarno Sutarno   +3 more
openalex   +1 more source

Development of Arduino-Based Rotating Wheel as a Physics Learning Media of Circular Motion [PDF]

open access: gold, 2022
Maharani Ayu Nurdiana Putri   +3 more
openalex   +1 more source

Relativistic Fluid Dynamics: Physics for Many Different Scales

open access: yesLiving Reviews in Relativity, 2007
The relativistic fluid is a highly successful model used to describe the dynamics of many-particle, relativistic systems. It takes as input basic physics from microscopic scales and yields as output predictions of bulk, macroscopic motion.
Comer Gregory L., Andersson Nils
doaj  

Mobile Application Development as Physics Learning Resource on The Topics of Circular Motion [PDF]

open access: gold, 2020
Johannes V.D. Wirjawan   +4 more
openalex   +1 more source

Enhanced Trajectory Forecasting for Hypersonic Glide Vehicle via Physics-Embedded Neural ODE

open access: yesDrones
Forecasting hypersonic glide vehicle (HGV) trajectories accurately is crucial for defense, but traditional methods face challenges due to the scarce real-world data and the intricate dynamics of these vehicles.
Shaoning Lu, Yue Qian
doaj   +1 more source

Natural Reference Frames within Video Analysis [PDF]

open access: yesarXiv
This study explores an alternative approach to video-based motion analysis using natural reference frames rather than relying on manual alignment. We demonstrate how the motion data itself can reveal optimal reference frames, connecting fundamental physical principles with data analysis.
arxiv  

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