Ruled Path Planning Framework for Safe and Dynamic Navigation
Alexandre Cardaillac, Martin Ludvigsen · OCEANS 2021: San Diego – Porto · 2021
The need for vehicle autonomy is constantly increasing, requiring increased load of on-board processing. However, most of low-cost agents are not able to handle the workload in real-time. In this paper, a path planning framework is presented for safe and dynamic navigation in multi-dimension environments. It is design to minimise the computational power required while remaining able to quickly adapt. For this, a highly Paramatrised Rapidly-exploring Random Graph (PRRG) is developed along side a system of rules allowing dynamic node selection and the D* Lite search algorithm to create the path. All of the graph parameters can be changed dynamically, making the graph able to adapt to the environment in real-time. Eventually, an extension for custom node generation is proposed, enabling specific routes to be created online which is especially relevant for survey and inspection applications. Although this framework was made for navigation of Autonomous Underwater Vehicles (AUVs), it can find applications to other domains such as navigation of Unmanned Aerial Vehicles (UAVs). The capabilities of the framework are demonstrated considering an underwater ship hull inspection scenario and confirmed its usefulness and effectiveness for real-time operations.