Research on Positioning and Navigation System of Greenhouse Mobile Robot Based on Multi-Sensor Fusion.

The labor shortage and rising costs in the greenhouse industry have driven the development of automation, with the core of autonomous operations being positioning and navigation technology. However, precise positioning in complex greenhouse environments and narrow aisles poses challenges to localization technologies. This study proposes a multi-sensor fusion positioning and navigation robot based on ultra-wideband (UWB), an inertial measurement unit (IMU), odometry (ODOM), and a laser rangefinder (RF).

Eliminating Primacy Bias in Online Reinforcement Learning by Self-Distillation.

Excessive invalid explorations at the beginning of training lead deep reinforcement learning process to fall into the risk of overfitting, further resulting in spurious decisions, which obstruct agents in the following states and explorations. This phenomenon is termed primacy bias in online reinforcement learning. This work systematically investigates the primacy bias in online reinforcement learning, discussing the reason for primacy bias, while the characteristic of primacy bias is also analyzed.

Synchronized 3D Printing and Corona Charging for One-Step Prototyping of Polarized Polylactic Acid Electrets.

Three-dimensional (3D) printing technology is advantageous in the fast prototyping of complex structures, but its utilization in functional material fabrication is still limited due to a lack of activation capability. To fabricate and activate the functional material of electrets, a synchronized 3D printing and corona charging method is presented to prototype and polarize polylactic acid electrets in one step. By upgrading the 3D printer nozzle and incorporating a needle electrode to apply high voltage, parameters such as needle tip distance and applied voltage level were compared and optimized.

A Vegetable Leaf Disease Identification Model Based on Image-Text Cross-Modal Feature Fusion.

In view of the differences in appearance and the complex backgrounds of crop diseases, automatic identification of field diseases is an extremely challenging topic in smart agriculture. To address this challenge, a popular approach is to design a Deep Convolutional Neural Network (DCNN) model that extracts visual disease features in the images and then identifies the diseases based on the extracted features. This approach performs well under simple background conditions, but has low accuracy and poor robustness under complex backgrounds.

A Plant Disease Recognition Method Based on Fusion of Images and Graph Structure Text.

The disease image recognition models based on deep learning have achieved relative success under limited and restricted conditions, but such models are generally subjected to the shortcoming of weak robustness. The model accuracy would decrease obviously when recognizing disease images with complex backgrounds under field conditions. Moreover, most of the models based on deep learning only involve characterization learning on visual information in the image form, while the expression of other modal information rather than the image form is often ignored.

The realization of quantum anomalous Hall effect in two dimensional electron gas.

The quantum anomalous Hall effect (QAHE), carrying dissipationless chiral edge states, occurs without any magnetic field. Two main strategies were proposed to host QAHE: the magnetic topological insulator thin films and graphene systems. Only the former one was realized in experiment at low temperature.

Spatial-Temporal Characteristics of Confined Polymer Motion Determine Proton Conduction of Polyoxometalate-Poly(ethylene glycol) Hybrid Nanocomposites.

Highly efficient proton conductors, polyoxometalate-poly(ethylene glycol) (POM-PEG) hybrid nanocomposites, have been synthesized by encapsulating a single PEG chain inside the 1D nanochannel defined by the frameworks of POMs. By employing two types of neutron scattering techniques complemented by thermal analysis, we prove that in a nanochannel a single PEG chain stays as a distorted helix. More importantly, we reveal that the PEG segments perform a localized longitudinal random walk and quantitatively show the strong correlation between the local motion of PEG and the macroscopic proton conduction of the material.

Charge-Storage Aromatic Amino Compounds for Nonvolatile Organic Transistor Memory Devices.

Here, charge-storage nonvolatile organic field-effect transistor (OFET) memory devices based on interfacial self-assembled molecules are proposed. The functional molecules contain various aromatic amino moieties (N-phenyl-N-pyridyl amino- (PyPN), N-phenyl amino- (PN), and N,N-diphenyl amino- (DPN)) which are linked by a propyl chain to a triethoxysilyl anchor group and act as the interface modifiers and the charge-storage elements. The PyPN-containing pentacene-based memory device (denoted as PyPN device) presents the memory window of 48.