Results 71 to 80 of about 56,025 (214)
A Sparse-Array Design Method Using Q Uniform Linear Arrays for Direction-of-Arrival Estimation. [PDF]
Sensors (Basel), 2023 Zhang J, Xu H, Ba B, Mei F.
europepmc +1 more source
Advanced Materials Technologies, EarlyView.A THz metasurface device integrating a metal–dielectric–metal resonator with microwall‐defined recessed regions enables spatially guided, label‐free sensing of micrometer‐scale plastic particles. The as‐fabricated devices exhibit distinct THz reflection resonances for 3.1‐µm polystyrene particles and a concentration‐dependent resonance‐frequency‐shift ...
Naoki Inomata +2 more
wiley +1 more source
Advanced Robotics Research, EarlyView.Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley +1 more source
Colocated MIMO Radar Waveform-Array Joint Optimization for Sparse Array. [PDF]
Sensors (Basel), 2023 Yin J, Ma R, Lin M, Zhou S.
europepmc +1 more source
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 +8 more
wiley +1 more source
SAR 3D sparse imaging based on CLA
The Journal of Engineering, 2019 A novel method for synthetic aperture radar (SAR) three-dimensional (3D) sparse imaging based on a coprime linear array (CLA) is proposed. To reduce the geometric resolution loss caused by under-sampled sparse SAR, a jointed sparse imaging approach is ...
Bokun Tian +4 more
doaj +1 more source
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 +4 more
wiley +1 more source
Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
A Study on Capacitive Micromachined Ultrasonic Transducer Periodic Sparse Array. [PDF]
Micromachines (Basel), 2021 Zhang T +6 more
europepmc +1 more source
Push the Limits: Human‐Like Multimodal Extreme Embodied Intelligence for Autonomous Racing
Advanced Robotics Research, EarlyView.Autonomous racing tests embodied intelligence under extreme control limits of speed, actuation, and decision‐making. Inspired by human multimodality, we present Apex, an embodied agent deployed on a super‐formula racing car at Yas Marina. Integrating physics‐informed perception, multimodal learning, and tasking, Apex cuts lap times by 15% and achieves ...
Yanxin Zhou +13 more
wiley +1 more source