A FastSLAM Approach Integrating Beamforming Maps for Ultrasound-Based Robotic Inspection of Metal Structures

Othmane-Latif Ouabi (1) , Pascal Pomarede (1) , Matthieu Geist , Nico Declercq (1) , Cedric Pradalier (1)

1 Georgia Tech Lorraine [Metz]

We present a novel FastSLAM approach for a robotic system inspecting structures made of large metal plates. By taking advantage of the reflections of ultrasonic guided waves on the plate boundaries, it is possible to recover, with enough precision, both the plate shape and the robot trajectory. Contrary to our previous work, this approach takes into account the dispersive nature of guided waves in metal plates. This is leveraged to construct beamforming maps from which we solve the mapping problem through plate edges estimation for every particle, in a FastSLAM fashion. It will be demonstrated, with real acoustic measurements obtained on different metal plates, that such a framework achieves better results in terms of convergence and accuracy, while the complexity of the algorithm is sensibly reduced.

Domaines: Acoustique [physics.class-ph]

Othmane-Latif Ouabi, Pascal Pomarede, Matthieu Geist, Nico Declercq, Cedric Pradalier. A FastSLAM Approach Integrating Beamforming Maps for Ultrasound-Based Robotic Inspection of Metal Structures. IEEE Robotics and Automation Letters, 2021, 6 (2), pp.2908-2913. ⟨10.1109/LRA.2021.3062600⟩. ⟨hal-03468313⟩