This paper introduces a two-tier feedback control law for the path tracking of a mobile robot equipped with N on-axle trailers. Initially, through a recursive design process, the curvature-tracking challenge is converted into stabilizing the joint angles at predefined reference values. This design approach is straightforward and can be easily extended to configurations with multiple trailers. Using input-to-state stability analysis, we demonstrate the asymptotic stability of the closed-loop system, which is structured in cascade form. Furthermore, we reformulate the path-tracking problem as a curvature-planning challenge and propose an algorithm to determine the desired curvature for the tail trailer. The simulation results validate the effectiveness of this novel algorithm in truck-trailer systems.
Eliminating pathogen exposure is an important approach to control outbreaks of epidemics such as COVID-19 (coronavirus disease 2019). To deal with pathogenic environments, using disinfection robots is a practicable choice. This research formulates a 3D (three-dimensional) spatial disinfection strategy for a disinfection robot. First, a disinfection robot is designed with an extensible control framework for the integration of additional functions. The robot has eight degrees of freedom that can handle disinfection tasks in complex 3D environments where normal disinfection robots lack the capability to ensure complete disinfection. An ingenious clamping mechanism is designed to increase flexibility and adaptability. Secondly, a new coverage path planning algorithm targeted at the spraying area is used. This algorithm aims to achieve an optimal path via the rotating calipers algorithm after transformation between a 2D (two-dimensional) array and 3D space. Finally, the performance of the designed robot is tested through a series of simulations and experiments in various spaces that humans usually live in. The results demonstrate that the robot can effectively perform disinfection tasks both in computer simulation and in reality.