Path-Planning and Navigation for Robots Considering Human–Robot–Environment Interactions in Supermarket Environments

This study proposes a shopping assistant robot, called CartBot, to facilitate the grocery shopping experience for customers/shoppers. A grocery store environment can be complex and confusing to customers. Therefore, the main aim is to assist customers in navigating this environment efficiently while carrying their purchased items, and hence improve the overall shopping experience and reduce shopping time. To achieve this, a unified framework for implementing path planning and collision avoidance in a supermarket environment is proposed. Here, with a shopping list as the input, an efficient (or near-optimal) global path is generated to complete the shopping. Then, a real-time local planner is proposed to navigate this path while avoiding any obstacles that are encountered. Various features/strategies to facilitate navigation and obstacle interactions are also addressed in this work. Simulation studies of CartBot are carried out in a grocery store environment along with other CartBots, employees, and human shoppers to validate the performance of the proposed approach.