Results 211 to 220 of about 17,927 (312)
Taylor Series Interpolation-Based Direct Digital Frequency Synthesizer with High Memory Compression Ratio. [PDF]
Palomäki KI, Nurmi J.
europepmc +1 more source
Embedded flexible sensing technologies advance underwater soft robotics, yet most systems still suffer from hysteresis and limited perceptiveness. Instead, vision‐based tactile sensors provide reliable and rapid feedback essential for complex underwater tasks.
Qiyi Zhang +5 more
wiley +1 more source
An atomic clock synchronized versatile all-in-one digital 'LockBox'. [PDF]
Johnson S +5 more
europepmc +1 more source
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
High-Radix Taylor-Optimized Tone Mapping Processor for Adaptive 4K HDR Video at 30 FPS. [PDF]
Wang X, Lai Z, Chen L, An F.
europepmc +1 more source
Non-biological synthetic spike-in controls and the AMPtk software pipeline improve mycobiome data [PDF]
Jonathan M Palmer +3 more
openalex +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
LDF-BNN: A Real-Time and High-Accuracy Binary Neural Network Accelerator Based on the Improved BNext. [PDF]
Wan R, Cen R, Zhang D, Wang D.
europepmc +1 more source
CHARA/Silmaril Instrument Software and Data Reduction Pipeline: Characterization of the Instrument in the Lab and On-Sky [PDF]
Narsireddy Anugu +11 more
openalex +1 more source
Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang +5 more
wiley +1 more source

