3D SLAM (Simultaneous Localization and Mapping) is a technique for creating circumstance maps which are usable for measuring the environments and providing navigation information. One of the problems in 3D SLAM is computational efficiency of inserting new points into the circumstance map, since the efficiency is essential for keeping the quality and quantity of the obtained circumstance map and keeping the stability of the mapping procedure. This study focuses on how to improve the computational efficiency of 3D SLAM as a UGV (unmanned ground vehicle) application. We employ a sophisticated and well-organized 3D SLAM package, ETHZASL-ICP-Mapper, as a fundamental implementation. After analyzing the reason why the efficiency becomes decreased through the mapping procedure, we point out main two problems. Then we propose two approaches for overcoming these problems. The first approach is to divide the circumstance maps into sub-grid maps. The second approach is to alternate the k-d tree data structure in the point density control with a voxel grid data structure. The improvements are discussed based on the comparative experimental results.
In this paper, dealing with supply chain planning including distributors, manufacturers, and retailers, we consider distribution planning of distributors that order manufacturers to produce products and deliver the products to multiple retailers via warehouses. Although Calvete et al.(2014) dealt with a similar problem, we extend the problem into a two-stage model by taking into account uncertainty about demands of the retailers. To reduce losses due to the uncertainty, in the second stage the leftover inventories in some retailers are transshipped to retailers with residual demands after the demands are realized. We develop a computational method for obtaining an optimal solution of the extended two-stage model. Furthermore, assuming coordination of multiple distributors, we formulate a cooperative two-stage model in which the multiple distributors jointly place orders with the manufacturer and distribute the products to the retailers in a coordinated manner, and we allocate the total profit to each distributor using a solution concept of cooperative game theory. We demonstrate the validity of the proposed model through an illustrative numerical example.