High-precision positioning of robotic systems on programme trajectories using satellite navigation measurements

Abstract

Introduction. The main issue in processing satellite measurements remains the struggle with their interference, especially intensive in rugged terrain, cities, atmospheric disturbances and artificial interference. Use of satellite navigation in recent years shows that such conditions undermine traditional satellite signal processing methods based on the least squares method or its modifications. These algorithms are unable to provide the required accuracy of spatial orientation for mobile robotic systems operating under intensive disturbances of various physical nature. This requires new algorithms for processing stochastic information more efficient than the least squares method, in particular, based on the theory of nonlinear stochastic filtration. The main challenge in this case is the synthesis of equations of motion of robotic complexes invariant to its type and random conditions of the environment of its functioning. At the same time, as practice shows, the vast majority of complexes move along programme trajectories that allow for analytical description of their motion parameters, which creates prerequisites for solving the problem of synthesis of these equations.Materials and methods. This paper proposes a navigation algorithm for robotic systems moving along a given trajectory under random perturbing factors. The algorithm is based on the combination of nonlinear stochastic filtering methods for estimating the state of dynamic systems operating under disturbances with non-traditional algorithms for processing satellite measurements and electronic map data.Results. For an environmental monitoring robot system, the authors modelled the motion in the plane of the local meridian from an initial point with longitude 30° and latitude 45°. The paper analyses the accuracy of the developed algorithm by estimating the trajectory of the robotic system using two classes of satellite navigation systems: medium and low precision.Discussion and conclusion. The results of the numerical experiment together with the above-mentioned advantages of the proposed method allow us to consider its effective practical application for positioning of mobile robotic systems.

Keywords

• robotic systems
• satellite measurements
• electronic maps
• stochastic filtering
• extended kalman filter