R-DFS: A Coverage Path Planning Approach Based on Region Optimal Decomposition

Most Coverage Path Planning (CPP) strategies based on the minimum width of a concave polygonal area are very likely to generate non-optimal paths with many turns. This paper introduces a CPP method based on a Region Optimal Decomposition (ROD) that overcomes this limitation when applied to the path planning of an Unmanned Aerial Vehicle (UAV) in a port environment. The principle of the approach is to first apply a ROD to a Google Earth image of a port and combining the resulting sub-regions by an improved Depth-First-Search (DFS) algorithm. Finally, a genetic algorithm determines the traversal order of all sub-regions. The simulation experiments show that the combination of ROD and improved DFS algorithm can reduce the number of turns by 4.34%, increase the coverage rate by more than 10%, and shorten the non-working distance by about 29.91%. Overall, the whole approach provides a sound solution for the CPP and operations of UAVs in port environments.

Changes in Effective Playing Space When Considering Sub-Groups of 3 to 10 Players in Professional Soccer Matches

Success in soccer is much dependent on how players and teams create and restrict space and time. In match situations, players constitute small sub-groups to improve their collective synchronization and achievement of specific goals. This study aimed to identify changes in the effective playing space (EPS, defined as the smallest polygonal area delimited by the peripheral outfield players) when considering sub-groups of 3 to 10 players. Twenty outfield professional players participated in this study. The EPS, its regularity pattern (measured by the approximate entropy), coefficient of variation and players’ mean speed were calculated for sub-groups of 3, 4, 5, 6, 7, 8, 9 and 10 players, considering the smallest inter-player distance as the criterion. The EPS presented a most likely increase with a higher number of players, especially considering the transition from 3 to 4 players (~440% of variation, very large). As the EPS increased with the number of players, the correspondent regularity presented a trend of a most likely increase (from EPS3 vs. EPS4: ~25%, very large; to EPS9 vs. EPS10: ~11%, moderate). The mean speed results suggest that players may achieve different states of collective coordination, mainly between ~6 to 8 km.h-1. Overall, three different match scenarios should require additional attention when aiming to design more match transferable tasks: i) transition from EPS3 to EPS4; ii) transition from EPS4 up to EPS8; and iii) transition from EPS8 to EPS9. These results help to understand match self-organized behaviours and, consequently, allow to optimize task characteristics in practice sessions.