Solving Robotic Trajectory Sequential Writing Problem via Learning Character’s Structural and Sequential Information

The writing sequence of numerals or letters often affects aesthetic aspects of the writing outcomes. As such, it remains a challenge for robotic calligraphy systems to perform, mimicking human writers’ implicit intention. This article presents a new robot calligraphy system that is able to learn writing sequences with limited sequential information, producing writing results compatible to human writers with good diversity. In particular, the system innovatively applies a gated recurrent unit (GRU) network to generate robotic writing actions with the support of a prelabeled trajectory sequence vector. Also, a new evaluation method is proposed that considers the shape, trajectory sequence, and structural information of the writing outcome, thereby helping ensure the writing quality. A swarm optimization algorithm is exploited to create an optimal set of parameters of the proposed system. The proposed approach is evaluated using Arabic numerals, and the experimental results demonstrate the competitive writing performance of the system against state-of-the-art approaches regarding multiple criteria (including FID, MAE, PSNR, SSIM, and PerLoss), as well as diversity performance concerning variance and entropy. Importantly, the proposed GRU-based robotic motion planning system, supported with swarm optimization can learn from a small dataset, while producing calligraphy writing with diverse and aesthetically pleasing outcomes

Solving Robotic Trajectory Sequential Writing Problem via Learning Character’s Structural and Sequential Information

The writing sequence of numerals or letters often affects aesthetic aspects of the writing outcomes. As such, it remains a challenge for robotic calligraphy systems to perform, mimicking human writers’ implicit intention. This article presents a new robot calligraphy system that is able to learn writing sequences with limited sequential information, producing writing results compatible to human writers with good diversity. In particular, the system innovatively applies a gated recurrent unit (GRU) network to generate robotic writing actions with the support of a prelabeled trajectory sequence vector. Also, a new evaluation method is proposed that considers the shape, trajectory sequence, and structural information of the writing outcome, thereby helping ensure the writing quality. A swarm optimization algorithm is exploited to create an optimal set of parameters of the proposed system. The proposed approach is evaluated using Arabic numerals, and the experimental results demonstrate the competitive writing performance of the system against state-of-the-art approaches regarding multiple criteria (including FID, MAE, PSNR, SSIM, and PerLoss), as well as diversity performance concerning variance and entropy. Importantly, the proposed GRU-based robotic motion planning system, supported with swarm optimization can learn from a small dataset, while producing calligraphy writing with diverse and aesthetically pleasing outcomes

Cooperative Stabilization of the [Pyridinium-CO2-Co] Adduct on a Metal-Organic Layer Enhances Electrocatalytic CO2 Reduction.

Pyridinium has been shown to be a cocatalyst for the electrochemical reduction of CO2 on metal and semiconductor electrodes, but its exact role has been difficult to elucidate. In this work, we create cooperative cobalt-protoporphyrin (CoPP) and pyridine/pyridinium (py/pyH+) catalytic sites on metal-organic layers (MOLs) for an electrocatalytic CO2 reduction reaction (CO2RR). Constructed from [Hf6(μ3-O)4(μ3-OH)4(HCO2)6] secondary building units (SBUs) and terpyridine-based tricarboxylate ligands, the MOL was postsynthetically functionalized with CoPP via carboxylate exchange with formate capping groups. The CoPP group and the pyridinium (pyH+) moiety on the MOL coactivate CO2 by forming the [pyH+--O2C-CoPP] adduct, which enhances the CO2RR and suppresses hydrogen evolution to afford a high CO/H2 selectivity of 11.8. Cooperative stabilization of the [pyH+--O2C-CoPP] intermediate led to a catalytic current density of 1314 mA/mgCo for CO production at -0.86 VRHE, which corresponds to a turnover frequency of 0.4 s-1

Design and Experiment of Side-Shift Stubble Avoidance System for No-Till Wheat Seeder Based on Deviation-Perception Fusion Technology

To improve the stubble avoidance rate of no-till wheat seeders under the environment of corn stubble, the side-shift stubble avoidance system was developed in the present study based on deviation-perception fusion technology. Firstly, the amount of implement deviation compensation was accurately obtained by the information sensing system. Then, a fuzzy PID algorithm was proposed to optimize the performance of the control system. Finally, the simulation model of the control system was developed by Matlab/Simulink. The simulation results showed that the regulation time required for the system response curve to reach the steady state was 1.0 s, and the maximum overshoot was 8.2%. To verify the performance of the side-shift stubble avoidance system, an orthogonal test was conducted. The optimal combination of parameters was obtained, including the operation speed of 1.3 m/s, the hydraulic cylinder speed of 25 mm/s, and the straw mulch amount of 1.2 kg/m2. The field verification test was performed under the optimal parameters, showing the stubble avoidance rate was 90.6%, and the mean value of the sowing variation coefficient was 27.12%, which fully satisfied the requirements of stubble avoidance and sowing operation

Design Principles of Quinone Redox Systems for Advanced Sulfide Solid‐State Organic Lithium Metal Batteries

The emergence of solid-state battery technology presents a potential solution to the dissolution challenges of high-capacity small molecule quinone redox systems. Nonetheless, the successful integration of argyrodite-type Li6PS5Cl, the most promising solid-state electrolyte system, and quinone redox systems remains elusive due to their inherent reactivity. Here, a library of quinone derivatives is selected as model electrode materials to ascertain the critical descriptors governing the (electro)chemical compatibility and subsequently the performances of Li6PS5Cl-based solid-state organic lithium metal batteries (LMBs). Compatibility is attained if the lowest unoccupied molecular orbital level of the quinone derivative is sufficiently higher than the highest occupied molecular orbital level of Li6PS5Cl. The energy difference is demonstrated to be critical in ensuring chemical compatibility during composite electrode preparation and enable high-efficiency operation of solid-state organic LMBs. Considering these findings, a general principle is proposed for the selection of quinone derivatives to be integrated with Li6PS5Cl, and two solid-state organic LMBs, based on 2,5-diamino-1,4-benzoquinone and 2,3,5,6-tetraamino-1,4-benzoquinone, are successfully developed and tested for the first time. Validating critical factors for the design of organic battery electrode materials is expected to pave the way for advancing the development of high-efficiency and long cycle life solid-state organic batteries based on sulfides electrolytes