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Real-time robot topological localization and mapping with limited visual sampling in simulated buried pipe networks

Xiangyu S. Li, T. L. Nguyen, Anthony G. Cohn, Mehmet R. Doğar, Netta Cohen

发表年份
2023
引用次数
5
访问权限
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摘要

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.

关键词

Computer scienceTopological mapRobotKey (lock)Computer visionArtificial intelligenceLimitingSimultaneous localization and mappingMobile robotReal-time computing

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