Performance analysis of fast marching-based motion planning for autonomous mobile robots in ITER scenarios

Operations of transportation in cluttered environments require robust motion planning algorithms. Specially with large and heavy vehicles under hazardous operations of maintenance, such as in the ITER, an international nuclear fusion research project. The load transportation inside the ITER facilities require smooth and optimized paths with safety margin of 30 cm. The transportation is accomplished by large rhombic-like vehicles to exploit its kinematic capabilities. This paper presents the performance analysis of a motion planning algorithm to optimize trajectories in terms of clearance, smoothness and execution time in cluttered scenarios. The algorithm is an upgraded version of a previous one used in ITER, replacing the initialization implemented using Constrained Delaunay Triangulation by the Fast Marching Square. Exhaustive simulated experiments have been carried out in different levels of ITER buildings, comparing the performance of the algorithm using different metrics.