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Hierarchical motion planning method for space redundant manipulators with end-task constraint

A novel hierarchical motion planning method combines goal-biased RRT with sequential convex programming to plan high-quality trajectories for space redundant manipulators. The proposed method successfully satisfies obstacle avoidance, end-effector line-of-sight constraints, and joint torque limits, converging in 17 and 18 iterations fo...

SourceBeijing Institute of Technology Press Co., Ltd·JournalSpace: Science & Technology·DateAug 21, 2026

AI learns to build simple equations for complex systems

A new AI framework uncovers simple, understandable rules governing complex dynamics in nature and technology. The AI generates equations that accurately describe complex systems, revealing hidden variables that govern their behavior. This approach offers scientists a new way to leverage AI for understanding complex systems.

SourceDuke University·Journalnpj Complexity·DateDec 17, 2025

Malaria parasites move on right-handed helices

Researchers from Heidelberg University discovered that malaria parasites use right-handed helices to navigate through tissues, a key finding with implications for improving drug and vaccine testing. The parasite's asymmetrical body plan enables it to control its motion and transition between compartments more efficiently.

SourceHeidelberg University·JournalNature Physics·DateNov 24, 2025

From order to chaos: Understanding the principles behind collective motion in bacteria

Researchers discovered how bacterial swarms transition from organized movement to chaotic flow as confinement radius increases. The study reveals intermediate states between order and turbulence through large-scale experiments, computer modeling, and mathematical analysis. These findings provide insights into the universal properties o...

SourceInstitute of Science Tokyo·JournalProceedings of the National Academy of Sciences·TypeExperimental study·DateMar 17, 2025

ISS National Lab publication highlights groundbreaking physical science research in space

Researchers on the ISS National Lab have leveraged microgravity to study fundamental physical phenomena, such as heat transfer, combustion, and fluid dynamics. These discoveries hold potential for advances in pharmaceuticals, energy production, materials manufacturing, and more.

SourceInternational Space Station U.S. National Laboratory·JournalGravitational and Space Research·TypeMeta-analysis·DateNov 26, 2024

When it comes to neural networks learning motion, it’s all relative

Researchers developed a deep learning approach to recognize and predict motion using vector-based relative change in position. The method, VecNet+LSTM, scored higher than other frameworks in recognizing motion and predicting future movements. This study has implications for machine learning in video analysis and artificial intelligence.

SourceIntelligent Computing·JournalIntelligent Computing·TypeExperimental study·DateMar 29, 2023

Two-dimensional quantum freeze

Researchers from ETH Zurich have achieved groundbreaking cooling of a glass nanoparticle along two directions of motion, overcoming the 'Dark Mode Effect'. This breakthrough enables the creation of fragile quantum states and paves the way for ultrasensitive gyroscopes and sensors.

SourceUniversity of Innsbruck·JournalNature Physics·TypeExperimental study·DateMar 6, 2023

Theory sorts order from chaos in complex quantum systems

A new mathematical theory developed by Peter Wolynes and David Logan predicts the nature of motions in a chlorophyll molecule when it absorbs energy from sunlight. The findings suggest that there are exceptions where simple motions persist for long times, influencing processes like photosynthesis.

SourceUniversity of Illinois at Urbana-Champaign, News Bureau·JournalProceedings of the National Academy of Sciences·TypeComputational simulation/modeling·DateFeb 27, 2023

Theory can sort order from chaos in complex quantum systems

A new mathematical theory developed by scientists at Rice University and Oxford University can predict the nature of motions in complex quantum systems. The theory applies to any sufficiently complex quantum system and may give insights into building better quantum computers, designing solar cells, or improving battery performance.

SourceRice University·JournalProceedings of the National Academy of Sciences·TypeComputational simulation/modeling·DateFeb 23, 2023

A closer look at the dynamics of the p-Laplacian Allen–Cahn equation

A team of researchers from Korea investigated the dynamics of the p-Laplacian AC equation, finding that solutions maintain three criteria: phase separation, boundedness, and energy decay properties. They also identified an advantage of p-AC equation over classical Laplacian in adjusting interface sharpness.

SourceIncheon National University·JournalApplied Mathematics and Computation·TypeExperimental study·DateNov 21, 2022

Never too odd to learn how to swim

Researchers have developed a new formula for swimming based on their study of odd elasticity, allowing microswimmers to exhibit autonomously directional and deterministic motion. The team used Purcell's swimmer model to demonstrate that any odd elastic micromaterial can spontaneously generate locomotion in a fluid.

SourceKyoto University·JournalPhysical Review E·TypeComputational simulation/modeling·DateJun 6, 2022

Inferring the size of a collective of self-propelled Vicsek particles from the random motion of a single unit

Researchers at NYU Tandon School of Engineering propose a paradigm to solve the problem of inferring collective size from individual behaviors. By observing self-propelled Vicsek particles, they show that the time rate of growth of mean square heading is sufficient to predict the number of particles under particular parameters.

SourceNYU Tandon School of Engineering·JournalCommunications Physics·TypeData/statistical analysis·DateApr 11, 2022

Multi-functional electrostatic droplet tweezer remotely guides droplet motion

A research team from City University of Hong Kong developed a multi-functional electrostatic droplet tweezer that can precisely trap and remotely guide liquid droplets on flat and tilted surfaces, as well as in oil mediums. The technology offers precise and programmable droplet manipulation with high velocity and agile direction steering.

SourceCity University of Hong Kong·JournalProceedings of the National Academy of Sciences·TypeExperimental study·DateApr 1, 2022

NIST researchers link cutting-edge gravity research to safer operation of construction cranes

Researchers from NIST have developed a mathematical model that predicts the strength and timing of changes in velocity required for crane operators to apply when transporting heavy loads. This equation can be applied to various situations, including moving a load with initial rest and large distances.

SourceNational Institute of Standards and Technology (NIST)·JournalAmerican Journal of Physics·TypeComputational simulation/modeling·DateFeb 18, 2022

Numerical model of butterfly flight dynamics

A team of researchers from Shinshu University has developed a precise numerical model of butterfly flight dynamics, revealing the intricate relationship between wing movement and air flow. The study's findings have significant implications for designing micro air vehicles (MAVs), which could lead to breakthroughs in aerospace engineering.

SourceShinshu University·JournalBiology Open·TypeImaging analysis·DateFeb 14, 2022