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An optimal solution method based on 2-norm is proposed in this study to solve the inverse kinematics multiple-solution problem caused by a high redundancy. The current research also presents a motion optimization based on the 2-Norm of high-redundant mobile humanoid robots, in which a kinematic model is designed through the entire modeling.

The current study designs a highly redundant humanoid mobile robot with a differential mobile platform. The high-redundancy mobile humanoid robot consists of three modular parts (differential driving platform with two degrees of freedom (DOF), namely, left and right arms with seven DOF, respectively) and has total of 14 DOFs. Given the high redundancy of humanoid mobile robot, a kinematic model is designed through the entire modeling and an optimal solution extraction method based on 2-norm is proposed to solve the inverse kinematics multiple solutions problem. That is, the 2-norm of the angle difference before and after rotation is used as the shortest stroke index to select the optimal solution. The optimal solution of the inverse kinematics equation in the step is obtained by solving the minimum value of the objective function of a step. Through the step-by-step cycle in the entire tracking process, the kinematic optimization of the highly redundant humanoid robot in the entire tracking process is realized.

Compared with the before and after motion optimizations based on the 2-norm algorithm of the robot, its motion after optimization shows minimal fluctuation, improved smoothness, limited energy consumption and short path during the entire mobile tracking and operating process.

In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.

In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.

In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.

Motion optimization based on the 2-norm of a highly redundant humanoid mobile robot with the entire modeling is performed on the basis of the entire modeling. This motion optimization can make the highly redundant humanoid mobile robot’s motion path considerably short, minimize energy loss and shorten time. These researches provide a theoretical basis for the follow-up research of the service robot, including tracking and operating target, etc. Finally, the motion optimization algorithm is verified by the tracking and operating behaviors of the robot and an example.

Green energy as a transportation supply trend is irreversible. In this paper, a highway energy supply system (HESS) evolution model is proposed to provide highway transportation vehicles and service facilities with a clean electricity supply and form a new model of a source-grid-load-storage-charge synergistic highway-PV-WT integrated system (HPWIS). This paper aims to improve the flexibility index of highways and increase CO₂ emission reduction of highways.

To maximize the integration potential, a new energy-generation, storage and information-integration station is established with a dynamic master–slave game model. The flexibility index is defined to evaluate the system ability to manage random fluctuations in power generation and load levels. Moreover, CO₂ emission reduction is also quantified. Finally, the Lianhuo Expressway is taken as an example to calculate emission reduction and flexibility.

The results show that through the application of the scheduling strategy to the HPWIS, the flexibility index of the Lianhuo Expressway increased by 29.17%, promoting a corresponding decrease in CO₂ emissions.

This paper proposed a new model to capture the evolution of the HESS, which provides highway transportation vehicles and service facilities with a clean electricity supply and achieves energy transfer aided by an energy storage system, thus forming a new model of a transportation energy system with source-grid-load-storage-charge synergy. An evaluation method is proposed to improve the air quality index through the coordination of new energy generation and environmental conditions, and dynamic configuration and dispatch are achieved with the master–slave game model.

Owing to increased energy demands, China has become the world’s top CO2 emitter, with electricity generation accounting for the majority of emissions. Therefore, the Chinese Government aspires to achieve a low-carbon transformation of the electric industry by enhancing its green innovation capacity. However, little attention has been paid to the green development of electric technology. Thus, this paper aims to uncover the spatiotemporal evolution of electric technology in the context of China’s low-carbon transformation through patent analysis.

Using granted green invention patent data for China’s electric industry between 2000 and 2021, this paper conducted an exploratory, spatial autocorrelation and time-varying difference-in-differences (DID) analysis to reveal the landscape of electric technology.

Exploratory analysis shows that the average growth rate of electric technology is 8.1%, with spatial heterogeneity, as there is slower growth in the north and west and faster growth in the south and east. In addition, electric technology shows spatial clustering in local areas. Finally, the time-varying DID analysis provides positive evidence that low-carbon policies improve the green innovation capacity of electric technology.

The different effects of the low-carbon pilot policy (LCPC) on R&D subjects and the LCPC’s effectiveness in enhancing the value of patented technology were not revealed.

This paper reveals the spatiotemporal evolutionary characteristics of electric technology in mainland China. The results can help the Chinese Government clarify how to carry out innovative development in the electric industry as part of the low-carbon transformation and provide a theoretical basis and research direction for newcomers in this field.