In this paper, we propose a novel tabu search (NTS) algorithm that improves the efficiencies of picking goods of automated guided vehicles (AGVs) in an automatic warehouse by solving the conflicts that happen when multiple AGVs work at the same time. Relocation and exchanging operations are designed for the neighborhood searching process based on each pickup-point’s location in the warehouse, along with the initial solution generation and the termination condition in the proposed algorithm. The experimental results show that the tabu search algorithm can effectively optimize the order of pickup points, which could further reduce the total travel distance and improve the efficiencies of AGVs in automatic warehouses.

For the split delivery vehicle routing problem in the distribution link of logistics where the optimization objective is to minimize the total distance of the transportation path, a hybrid discrete differential evolution (HDDE) algorithm is adopted in this study. The algorithm applies the encoding and decoding method based on the remaining vehicle capacity to split the demand of customer point and adjust the splitting node to the optimal position of its path. In order to avoid the prematurity of the algorithm, the perturbation mechanism is added, i.e., the three-point insertion method is used in the crossover stage. To ensure the higher quality of the solution, the idea of tabu search is introduced in three cases: initial population generation, selection operation and local optimal situation. Finally, through the numerical experiments based on benchmark data, the HDDE algorithm is compared with other competitive algorithms to demonstrate its domination.

For the multiple automated guided vehicle (multi-AGV) routing problems in the warehousing link of logistics, where the optimization objective is to minimize both the number of AGVs used and the maximum pickup time simultaneously, a nondominant sorting differential evolution (NSDE) algorithm is proposed. In the encoding and decoding stages, the pickup point area is divided. AGVs are allocated to each region according to the proposed rule based on avoiding duplicate paths. Meanwhile, the pickup points within the region can be adjusted to optimize the pickup paths and improve the pickup efficiency. The fast nondominated sorting method and elitist selection strategy in the nondominated sorting genetic algorithm II (NSGA-II) are introduced into the differential evolution algorithm, which sorts all the regions to obtain the best Pareto solution set. Lastly, the domination of the proposed NSDE algorithm in Pareto frontier evaluation indicators is verified by some numerical experiments.

High-precision pose estimation using fiducial markers has many applications in medical device tracking, virtual reality alignment, navigation, and more. However, the accuracy of pose estimation and detection capabilities are often constrained by the shape and scale of the fiducial marker plane. In this article, we propose a triangular planar fiducial marker affixed to a positive icosahedron for pose estimation. This design expands the angular observation range, increases the marker scale, and consequently enhances estimation accuracy and recognition distance. The 2-D coordinates of the feature points from the markers are detected and extracted from the environment. Subsequently, the 3-D coordinates of these feature points are obtained using the triangulation method. This process results in the formation of 2-D–3-D point pairs. High-quality interior points are then filtered using the random sample consensus (RANSAC) method. The initial position is determined through the efficient perspective-n-point (EPnP) method, followed by the application of Levenberg–Marquardt (LM) optimization. We evaluated the performance of IcoTag3D through both simulations and physical experiments. The results from the simulation experiments indicate that IcoTag3D exhibits significantly lower maximum rotation angle error, reprojection error, and translation error at the submillimeter level. In addition, it demonstrates an improved recognition distance compared with the method of attaching ArUco markers to icosahedra. Physical experiments have further confirmed the feasibility of IcoTag3D.