This paper proposes a new path planning strategy called the navigation strategy with path priority (NSPP) for multiple robots moving in a large flat space. In the space, there may be some static or/and dynamic obstacles. Suppose we have the path-priority order for each robot, then this article aims to find an efficient path for each robot from its starting point to its target point without any collision. Here, a generalized Voronoi diagram (GVD) is used to perform the map division based on each robot’s path-priority order, and the proposed NSPP is used to do the path planning for the robots in the space. This NSPP can be applied to any number of robots. At last, there are several simulations with a different number of robots in a circular or rectangular space to be shown that the proposed method can complete the task effectively and has better performance in average trajectory length than those by using the benchmark methods of the shortest distance algorithm (SDA) and reciprocal orientation algorithm (ROA).

Calcaneal fractures often occur because of accidents during exercise or activities. In general, the detection of the calcaneal fracture is still carried out manually through CT image observation, and as a result, there is a lack of precision in the analysis. This paper proposes a computer-aid method for the calcaneal fracture detection to acquire a faster and more detailed observation. First, the anatomical plane orientation of the tarsal bone in the input image is selected to determine the location of the calcaneus. Then, several fragments of the calcaneus image are detected and marked by color segmentation. The Sanders system is used to classify fractures in transverse and coronal images into four types, based on the number of fragments. In sagittal image, fractures are classified into three types based on the involvement of the fracture area. The experimental results show that the proposed method achieves a high precision rate of 86%, with a fast computational performance of 133 frames per second (fps), used to analyze the severity of injury to the calcaneus. The results in the test image are validated based on the assessment and evaluation carried out by the physician on the reference datasets.

This paper proposes a new path planning method called the priority order navigation algorithm (PONA) for multi-robot navigation in a large flat space. The PONA can guarantee collision-free and efficient travel in the space with fixed or/and dynamic obstacles. The priority order of robots is assigned by the user based on the importance degree of the robots’ tasks and the objective is to make the higher priority robot reach its target faster than the lower priority robot. This study uses the generalized Voronoi diagram (GVD) to establish the initial map for PONA and links the navigation points in GVD to plan the path for each robot. Further, we modify the navigation point links to shorten feasible paths for the lower priority robot and its shortest two feasible paths can be switched to each other based on a certain condition to avoid hitting the higher priority robot. The proposed PONA is compared to several benchmark path planning methods, which are the shortest distance algorithm (SDA) and reciprocal orientation algorithm (ROA), in the simulation section and it is found that the PONA can reduce the average length of the trajectory by more than 10% compared with ROA and SDA.