Mechanical Analysis and Performance Optimization for the Lunar Rover’s Vane-Telescopic Walking Wheel

It is well-known that optimizing the wheel system of lunar rovers is essential.However,this is a difficult task due to the complex terrain of the moon and limited resources onboard lunar rovers.In this study,an experimental prototype was set up to analyze the existing mechanical design of a lunar rover and improve its performance.First,a new vane-telescopic walking wheel was proposed for the lunar rover with a positive and negative quadrangle suspension,considering the complex terrain of the moon.Next,the performance was optimized under the limitations of preserving the slope passage and minimizing power consumption.This was achieved via analysis of the wheel force during movement.Finally,the effectiveness of the proposed method was demonstrated by several simulation experiments.The newly designed wheel can protrude on demand and reduce energy consumption;it can be used as a reference for lunar rover development engineering in China.

A Brief Introduction on Joint Radar and Communication Systems

Joint radar and communication(JRC)technology is gradually becoming an essential approach to alleviating spectral congestion.Radar and communications systems were designed with common spectral and hardware resources to reduce size,improve performance,reduce cost,and decongest the spectrum.Various approaches have been proposed to achieve the coexistence of radar and communication systems.This paper mainly focuses on the research directions of radar communication coexistence(RCC)and dual-function radar communication systems(DFRC)in JRC technology.We summarize and analyze the existing research problems in the JRC era.According to the characteristics and advantages of JRC technology,we highlight several potentials in military and commercial applications.

A Biomimetic Model of Fiber-reinforced Composite Materials

In thjs paper. bamboo fiber has been. on micro scale. investigated as a helical. multi-layered hollow cylinder, the stiffness featu res of bamboo bast fiber were compared with those of a multifilament yarn in traditional fiber-reinforced composite materials, Moreover. a biomimetic model of the reinforce ment of fiber-reinforced composite materials was proposed by imitating the fine structure of bamboo bast fiber. The results show that the comprehensive stiffness properties of the cornplicated fine struc ture of bamboo fiber is superior over those of traditional fiber-reinforced composites.

Lane-change path planning and control method for self-driving articulated trucks

Purpose–This study aims to develop an automatic lane-change mechanism on highways for self-driving articulated trucks to improve traffic safety.Design/methodology/approach–The authors proposed a novel safety lane-change path planning and tracking control method for articulated vehicles.A double-Gaussian distribution was introduced to deduce the lane-change trajectories of tractor and trailer coupling characteristics of intelligent vehicles and roads.With different steering and braking maneuvers,minimum safe distances were modeled and calculated.Considering safety and ergonomics,the authors invested multilevel self-driving modes that serve as the basis of decision-making for vehicle lane-change.Furthermore,a combined controller was designed by feedback linearization and single-point preview optimization to ensure the path tracking and robust stability.Specialized hardware in the loop simulation platform was built to verify the effectiveness of the designed method.Findings–The numerical simulation results demonstrated the path-planning model feasibility and controller-combined decision mechanism effectiveness to self-driving trucks.The proposed trajectory model could provide safety lane-change path planning,and the designed controller could ensure good tracking and robust stability for the closed-loop nonlinear system.Originality/value–This is a fundamental research of intelligent local path planning and automatic control for articulated vehicles.There are two main contributions:thefirst is a more quantifiable trajectory model for self-driving articulated vehicles,which provides the opportunity to adapt vehicle and scene changes.The second involves designing a feedback linearization controller,combined with a multi-objective decision-making mode,to improve the comprehensive performance of intelligent vehicles.This study provides a valuable reference to develop advanced driving assistant system and intelligent control systems for self-driving articulated vehicles.