As one of the most essential earth-moving equipment, cable shovels significantly influence the efficiency and economy in the open-pit mining industry. The optimal digging trajectory planning for each cycle is the base for achieving effective and energy-saving operation, especially for robotic excavation, in which case, the digging trajectory can be precisely tracked. In this paper, to serve the vision of cable shovel automation, a two-phase multi-objective genetic algorithm was established for optimal digging trajectory planning. To be more specific, the optimization took digging time and energy consumption per payload as objects with the constraints of the limitations of the driving system and geometrical conditions. The WK-55-type cable shovel was applied for the validation of the effectiveness of the multi-objective optimization method for digging trajectories. The digging performance of the WK-55 cable shovel was tested in the Anjialing mining site to establish the constraints. Besides, the digging parameters of the material were selected based on the tested data to make the optimization in line with the condition of the real digging operations. The optimization results for different digging conditions indicate that the digging time decreased from an average of $20\mathrm{s}$ to $10\mathrm{s}$ after the first phase optimization, and the energy consumption per payload reduced by $\mathrm{13.28\%}$ after the second phase optimization, which validated the effectiveness and adaptivity of the optimization algorithm established in this paper.

Vehicle seats have a significant impact on the comfort of passengers. The development of seats is a field in which scholars are widely concerned. In this study, we add an electromagnetic levitation structure and design a new active seat suspension based on the passive seat suspension. Then, simulation research is carried out based on a C-level road surface combined with integral sliding mode control and state feedback control. The results show that both state feedback control and integral sliding mode control positively affect vehicle seat vibration reduction, and integral sliding mode control has a better anti-interference effect than state feedback control. At the same time, it is proved that the seat suspension has good working characteristics and economy.

In this paper, the self-assembly process of diblock copolymers confined in multi-walled cylindrical nanotubes is systematically investigated using a molecular dynamics (MD) method. The dependence of resultant morphologies on the degree of confinement and on the interaction strength between nanotubes and copolymers is studied comprehensively. When the wall surfaces are not preferential, results indicate that geometric confinement significantly influences copolymer conformations. In addition, the thickness of the helical lamellar structure increases with interaction strength and confinement size. In cases where the nanotubes are strongly attracted to one copolymer block, the confinement effect weakens as geometric space increases. Findings explain the dependence of chain conformation on the degree of confinement and the strength of surface preferences.