Constraint-based solid modeling is the kernel part of current CADsystems. It has been widely used in supporting detailed design and variational design. However, it cannot support early stage design and is not easy-to-...Constraint-based solid modeling is the kernel part of current CADsystems. It has been widely used in supporting detailed design and variational design. However, it cannot support early stage design and is not easy-to--use becauseit demands fully detailed input description of a design. To solve these problems,researchers attempt to incorporate virtual reality techniques into geometric modeling systems. This paper presents a novel approach for interactive constraint-basedsolid modeling in a virtual reality environment. The approach allows the designerto construct and edit a constraint-based solid model by direct 3D manipulations,and ensures the created solid model to be precise by recognizing and solving geometric constraints. To effectively support 3D manipulations and change propagation,a new constraint-based solid model is adopted. In the model, besides the normalconstituents of the typical constraint-based solid model, some new attributes likeshape control points, location pattern and explicit shape constraints of a primitiveare defined. Guided by the location pattern, our algorithms for recognizing andsolving location constraints are real-time.展开更多
目前基于蚁群算法的路径规划用于多约束条件下寻找最优路径时,容易陷入局部最优解并导致收敛速度慢.为此,在路径长度、有效景点区域数量、路径平滑性和路径障碍距离等约束条件下,构造一种适应度函数模型,以评价漫游路径的质量.提出混合...目前基于蚁群算法的路径规划用于多约束条件下寻找最优路径时,容易陷入局部最优解并导致收敛速度慢.为此,在路径长度、有效景点区域数量、路径平滑性和路径障碍距离等约束条件下,构造一种适应度函数模型,以评价漫游路径的质量.提出混合细菌觅食优化思想的改进蚁群优化(bacterial foraging optimization and ant colony optimization,BFO-ACO)算法,采用禁忌表优化策略解决传统蚁群算法的死锁问题,提高算法初期的路径多样性,通过引入细菌觅食算法的复制和驱散机制,提高收敛速度,跳出局部最优值.实验结果表明,BFO-ACO算法可在多约束环境下以较少的迭代次数获得高质量的漫游路径,为漫游路径设计提供了参考.展开更多
文摘Constraint-based solid modeling is the kernel part of current CADsystems. It has been widely used in supporting detailed design and variational design. However, it cannot support early stage design and is not easy-to--use becauseit demands fully detailed input description of a design. To solve these problems,researchers attempt to incorporate virtual reality techniques into geometric modeling systems. This paper presents a novel approach for interactive constraint-basedsolid modeling in a virtual reality environment. The approach allows the designerto construct and edit a constraint-based solid model by direct 3D manipulations,and ensures the created solid model to be precise by recognizing and solving geometric constraints. To effectively support 3D manipulations and change propagation,a new constraint-based solid model is adopted. In the model, besides the normalconstituents of the typical constraint-based solid model, some new attributes likeshape control points, location pattern and explicit shape constraints of a primitiveare defined. Guided by the location pattern, our algorithms for recognizing andsolving location constraints are real-time.
文摘目前基于蚁群算法的路径规划用于多约束条件下寻找最优路径时,容易陷入局部最优解并导致收敛速度慢.为此,在路径长度、有效景点区域数量、路径平滑性和路径障碍距离等约束条件下,构造一种适应度函数模型,以评价漫游路径的质量.提出混合细菌觅食优化思想的改进蚁群优化(bacterial foraging optimization and ant colony optimization,BFO-ACO)算法,采用禁忌表优化策略解决传统蚁群算法的死锁问题,提高算法初期的路径多样性,通过引入细菌觅食算法的复制和驱散机制,提高收敛速度,跳出局部最优值.实验结果表明,BFO-ACO算法可在多约束环境下以较少的迭代次数获得高质量的漫游路径,为漫游路径设计提供了参考.
