چكيده به لاتين
The main purpose of this study is to provide an innovative filter to improve the estimation of the position of the moving robot in the indoor environment and also to deal with the effect of the robotic phenomenon in locating this type of robot. In this study, while analyzing and providing a solution based on particle population optimization algorithm to overcome the two main problems of particle filters, namely particle decay and poverty, the robot's inability to regain its position when applying sudden inputs as uncertainty of input type. The unknown is suddenly recognized and is an intrinsic problem with particle filters, leading to a robotic phenomenon. In the proposed method, an innovative algorithm is used to distribute the particles in the state space, which can propagate the particles in areas with high probability when applying sudden and large control inputs to the robot, and provide a good estimate of the robot's position. Prevent the occurrence of a robotic phenomenon. In addition, this dissertation explains and compares some of the work done in the field of particle filters to improve the two problems of particle decay and poverty. Finally, the proposed algorithm is tested.
