MOLECULAR-GEOMETRY AND CHAIN ENTANGLEMENT - PARAMETERS FOR THE TUBE MODEL

The tube diameter in the reptation model is the distance between a given chain segment and its nearest segment in adjacent chains. This dimension is thus related to the cross-sectional area of polymer chains and the nearest approach among chains, without effects of thermal fluctuation and steric repulsion. Prior calculated tube diameters are much larger, about 5 times, than the actual chain cross-sectional areas. This is ascribed to the local freedom required for mutual rearrangement among neighboring chain segments. This tube diameter concept seems to us to infer a relationship to the corresponding entanglement spacing. Indeed, we report here that the critical molecular weight, M(c), for the onset of entanglements is found to be M(c) = 28 A/([R2]0/M), where A is the chain cross-sectional area and [R2]0 the mean-square end-to-end distance of a freely jointed chain of molecular weight M. The new, computed relationship between the critical number of backbone atoms for entanglement and the chain cross-sectional area of polymers, N(c) = A0,44, is concordant with the cross-sectional area of polymer chains being the parameter controlling the critical entanglement number of backbone atoms of flexible polymers.

基于实时障碍物预测的机器人运动规划

本文给出了移动机器人的虚力导航和运动规划系统．这种方法结合最小方差估计算法（ＬＭ ＳＥ）能有效地对机器人进行实时导航和避撞．在预测过程中，根据导航的不同阶段和预测误差的变化情况，采用Ｆｕｚｚｙ 规则动态地调整误差函数中的权重，使预测过程尽可能准确．导航算法的基本思想是首先通过预测算法来获得移动机器人的运动信息，然后虚力系统根据预测信息决定机器人的未来运动，仿真结果表明该方法实时性好，能准确躲避障碍物并且到达目标点

基于修正的最小均方误差分类算法的移动机器人运动规划

研究了不确定性环境下移动机器人躲避运动轨迹未知的移动障碍物的一种新方法．通过实时最小均方误差估计算法预测每个障碍物的位置及运动轨迹，并利用模式识别中最小均方误差分类器的修正模型计算出机器人的局部避障路径，再运用船舶导航中使用的操纵盘技术来确定每个导航周期中移动机器人的速．度仿真结果表明了该方法的可行性