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)
Introduction: Our work introduces a real-time robotic localization and mapping system for buried pipe networks. Methods: The system integrates non-vision-based exploration and navigation with an active-vision-based localization and topological mapping algorithm. This algorithm is selectively activated at topologically key locations, such as junctions. Non-vision-based sensors are employed to detect junctions, minimizing the use of visual data and limiting the number of images taken within junctions. Results: The primary aim is to provide an accurate and efficient mapping of the pipe network while ensuring real-time performance and reduced computational requirements. Discussion: Simulation results featuring robots with fully autonomous control in a virtual pipe network environment are presented. These simulations effectively demonstrate the feasibility of our approach in principle, offering a practical solution for mapping and localization in buried pipes.