Abstract
Professional cleaning and safe social distance monitoring are often considered as demanding, time-consuming, repetitive, and labor intensive tasks with the risk of getting exposed to the virus. Safe social distance monitoring and cleaning are an emerging problem solved through robotics solutions. This research aims to develop a safe social distance surveillance system on an intra-reconfigurable robot with a multi-robot cleaning system for large population environments like office buildings, hospitals, or shopping malls. We propose an adaptive multi-robot cleaning strategy based on zigzag based coverage path planning that works in synergy with the human interaction heat map generated by safe social distance monitoring systems. We further validate the proposed adaptive velocity model's efficiency for the multi-robot cleaning systems regarding time consumption and energy saved. The proposed method using sigmoid based nonlinear function has shown superior performance with 14.1 percent faster and energy consumption of 11.8 percent less than conventional cleaning methods. The outcome of the thesis is as follows. 1) Design and kinematic analysis of an Intra-reconfigurable robot with multi robot cleaning system. 2)Development of a full scale autonomous navigation and controls for multi robot system. 3) Development of vision based approach for estimating human interaction levels and heat map generation 4) Experimentation and validation for the proposed adaptive cleaning strategy with various velocity behaviour models with respect to time and energy consumption.