Real-time robot topological localization and mapping with limited visual sampling in simulated buried pipe networks - Li, Xiangyu S.; Nguyen, T. L.; Cohn, Anthony G.; Dogar, Mehmet; Cohen, Netta (Frontiers in Robotics and AI, 2023)
Our work presents a real-time robotic localization and mapping system designed for buried pipe networks. The system integrates non-vision-based exploration and navigation with an activevision-based localization and topological mapping algorithm that is activated only at topologically key locations, such as junctions. To minimize the use of visual data, non-vision-based sensors are used to detect junctions and to limit the number of images taken within junctions to a minimum.The aim is to provide an accurate and efficient mapping of the pipe network while ensuring real-time performance and reduced computational requirements. Simulation results of the robots with fully autonomous control in a virtual pipe network environment are presented, demonstrating the feasibility of this approach in principle and providing a practical solution for mapping and localization in buried pipes.