Yanyang Lu

To address the challenge of parallel parking in narrow environments, a multi‐segment path planning method is proposed for autonomous unmanned vehicles (AUVs), which integrates circular arc and dual clothoid curves, ensuring continuous path curvature and minimal longitudinal space occupancy. First, considering the narrow environmental constraints and the parameters of AUV, the planning for the preparatory phase path and the parking‐in phase path are completed, respectively. The role of the preparatory phase path is to guide the AUV to the target point, and the parking‐in phase path can guide the AUV into the target parking space. Then, by using the particle swarm optimization (PSO) algorithm with a penalty function framework, a multi‐constraint nonlinear programming path function model is established to seek out the parking path. Subsequently, the pure pursuit (PP) algorithm is employed to control the movement of AUV along the planned path. Finally, the simulation result and real‐vehicle experiment are conducted, which show that the parking path planning method proposed in this article enables AUV to safely complete parking operations in the narrow environment.

This paper designs a resilient stubborn observer for switched autonomous systems (SASs) with an energy harvesting sensor (EHS). In order to extend the lifespan of the sensor, a sensor with the ability of harvesting energy is used. For restraining the effect of measurement outliers, a stubborn observer is designed which includes a saturation function with the varying saturation levels. The observer gain fluctuation is considered which is dealt with by the resilience filtering scheme. The aim of this paper is, considering observer gain fluctuation, the measurement outliers and an EHS for SASs, to design a resilient stubborn observer which can guarantee the error dynamics to meet the given performance requirement. Specifically, the existence conditions are derived firstly and then the resilient stubborn observer is designed by linear matrix inequality (LMI) technology. At the end, the performance of the designed observer is evaluated through a numerical simulation and a set of comparative experiments are implemented to further signify the merits of the designed observer.