Collision Avoidance and Routing based on Location Access (CARLA) of mobile robots

Abstract

Abstract In this paper, a novel robotic system methodology known as Collision Avoidance and Routing based on Location Access (CARLA) is proposed. It is intended for use in environments like hospitals or crisis situations where quick action and the preservation of human life are crucial, and when the primary actuator is to protect the lives of healthcare workers and to prevent the high potential for viral transmission among patients, such as in COVID-19 isolation hospitals. Our framework is primarily concerned with accuracy and quick responses. E.g. delivering tools or items in a specific district while avoiding collisions with other robots or any surrounding obstacles. The suggested CARLA can also be used for a variety of related applications, including those found in factories, warehouses, and any other situation where mobile robots must be chosen and routed using a distant centralized control. The Robot Knowledge Module (RKM), Robot Selection Module (RSM), and Route Reservation Module (RRM) are the three core modules that make up the proposed framework, which will be explained in detail throughout the paper. In comparison to conventional techniques used in similar situations, the simulation results using the suggested framework demonstrate the flexible and effective mobility of the robots in terms of the robots' path computation time and the request's success rate without collision.