F.М. Tseeva , N.Е. Arabov , А.М. Bozieva , Z. V. Shomakhov
2026-04-29
Abstract ▼
The relevance of this research is driven by the growing need for safe validation of navigation algorithms for autonomous mobile robots operating in cluttered and dynamically changing environments, where the use of physical equipment entails risks of damage and high costs. The aim of the work is to develop a rigorous methodology for software emulation of a technical vision system based on complementary virtual infrared and ultrasonic sensors. To achieve this aim, the following tasks were solved: formalization of the kinematic model of a differential drive with a state vector [x, y, θ]ᵀ; mathematical description of nonlinear triangulation for IR sensors and the physics of ultrasound propagation using the time-of-flight method d = c·t/2; integration of additive Gaussian noises with parameters σus = 0.005 m, σir = 0.002 m; implementation of heterogeneous data fusion using an Unscented Kalman Filter. The navigation controllers employed were the artificial potential field method with attractive and repulsive components, and fuzzy logic controllers. Experimental validation in a Python simulation environment of a maze with static obstacles demonstrated an average positioning error of 0.2 m in spherical configurations and an obstacle detection accuracy of 89.61%. The novelty of the proposed approach lies in providing a deterministic link between theoretical trajectory planning and physical implementation through the synergistic use of optical and acoustic sensory modalities. The practical significance of the work consists in a substantial reduction in the development and testing time for intelligent robotic systems, owing to the possibility of preliminary debugging of perception, data fusion, and navigation algorithms in controlled emulation conditions without the need for expensive hardware
