Results 171 to 180 of about 1,512,680 (298)

BoxStacker: Deep Reinforcement Learning for 3D Bin Packing Problem in Virtual Environment of Logistics Systems. [PDF]

Sensors (Basel), 2023
Murdivien SA, Um J.
europepmc   +1 more source

From Rigid to Soft Robotic Approaches for Neuroendoscopy

Advanced Robotics Research, EarlyView.
Robotic assistance has had minimal impact on deep intraventricular surgeries, where small‐scale, precision, and reduced invasiveness can contribute to improved patient outcomes. Emerging technologies in rigid, soft, and hybrid robotics are reviewed to identify the most promising mechanisms for deep brain navigation in addition to an attempt to identify
Kieran Gilday, Irena Zubak, Andreas Raabe, Josie Hughes   +3 more
wiley   +1 more source

Poststroke Neurorehabilitation Using a Soft Robotic Glove Combined With a Virtual Environment: Preliminary Study on Feasibility, Safety, Effects, and User Satisfaction. [PDF]

JMIR Neurotechnol
Proulx CE, Higgins J, Vaughan T, Hewko M, Gagnon DH.   +4 more
europepmc   +1 more source

Learning in a Virtual Environment to Improve Type 2 Diabetes Outcomes: Randomized Controlled Trial. [PDF]

JMIR Form Res, 2023
Johnson CM, D'Eramo Melkus G, Reagan L, Pan W, Amarasekara S, Pereira K, Hassell N, Nowlin S, Vorderstrasse A.   +8 more
europepmc   +1 more source

Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics

Advanced Robotics Research, EarlyView.
This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang, Zhipeng Jiang, Sun Hwa Kwon, Matthew Ibrahim, Alexander Dang, Lin Dong   +5 more
wiley   +1 more source

Consumption of a diet high in fat and sugar is associated with worse spatial navigation ability in a virtual environment. [PDF]

Int J Obes (Lond)
Tran DMD, Double KS, Johnston IN, Westbrook RF, Harris IM.   +4 more
europepmc   +1 more source

Editorial: Perceptual Motor Control in the Virtual Environment and Its Implications in the Real World. [PDF]

Front Sports Act Living, 2023
Ida H, Fukuhara K, Mohapatra S, Sekiguchi H.   +3 more
europepmc   +1 more source

Information Transmission Strategies for Self‐Organized Robotic Aggregation

Advanced Robotics Research, EarlyView.
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng, Zihan Li, Yifeng Shao, Jinhao Liu, Li Yu, Shuguang Li   +5 more
wiley   +1 more source

Evaluating the effects of a programming error on a virtual environment measure of spatial navigation behavior. [PDF]

J Exp Psychol Learn Mem Cogn, 2023
Weisberg SM, Schinazi VR, Ferrario A, Newcombe NS.   +3 more
europepmc   +1 more source

Formation Control of Multi‐Agent System with Local Interaction and Artificial Potential Field

Advanced Robotics Research, EarlyView.
This article proposes a local interaction‐based formation control method for Multi‐Agent system, integrating consensus and leader‐follower strategies with a stress response mechanism—artificial potential field to reduce communication overhead and enable obstacle avoidance. Experimental results on triangular, square, and hexagonal formations confirm its
Luoyin Zhao, Zheping Yan, Yuqing Wang, Raye Chen‐Hua Yeow   +3 more
wiley   +1 more source