Segway Navigation for Enhanced Efficiency and Optimized Mobility in Smart City Environment

Efficient and sustainable urban transportation necessitates innovative solutions for navigating narrow and constrained spaces, particularly given the growing utilization of smaller vehicles. This paper presents a set of new nonlinear time-invariant stabilizing acceleration-based controllers of a Segway robot modeled in 2D space in the presence of dynamical obstacles. The controllers are designed using the Lyapunov-based control, which is a modified artificial potential fields methodology. These controllers enable autonomous navigation of the Segway robot to reach its target in a dynamic environment. Rigorous mathematical proofs are provided to formally establish the stability and asymptotic controllability of the system, and the Segway reliably converges to its target. Computer simulations in Wolfram Mathematica 14.1 software numerically (RK4 method) verify the effectiveness of the controllers in replicating real smart city scenarios, such as navigating narrow passage ways and pedestrian pavements in the presence of static and dynamic obstacles. This theoretical work serves as a foundation for the development of a physical prototype for smart city environments.