Method of Formation of Quantitative Indicators of Complexity of the Environment by a Group of Autonomous Mobile Robots

Abstract

This article presents the methods that allow forming quantitative estimations of functional characteristics of a group of autonomous mobile robots (AMRs) and local areas of the environment surrounding it. The evaluation of the environment is based on the analysis of scattering of the cloud of obstacle points and made using the information formed by the computer vision system (CVS), which every robot in the group has. The core element of CSV is 3D lidar. Quantitative data about the complexity of the environment can be used for determining the optimal methods of solving the planning tasks and forming the patterns of group formation. Such data about the complexity of local areas of the environment can also be used for determining them as insurmountable for a single robot or a group of robots. The reason for such a decision can be the violation of safety rules and breaking of the group formation. The assessment of robots’ functional characteristics is performed based on the fuzzy model that consists of separate fuzzy classifiers; each of them allows obtaining a quantitative estimation of one of the parameters. The hierarchic structure of the used fuzzy model makes it significantly easier to synthesize and analyze it.