Underwater autonomous robotic operations require online localization and 3D mapping. Because of the absence of absolute positioning underwater, these tasks strongly rely on embedded sensors, including proprioceptive or navigation sensors - which can be fused for an odometry, - and exteroceptive sensors. One of the most popular exteroceptive sensors for underwater is the imaging sonar, which emits a large fan-shaped acoustic signal and estimates the position of the surrounding obstacles from a measure of the reflected signal. This paper addresses underwater online localization and 3D mapping using a forward looking, wide-aperture imaging sonar and vehicle's intrinsic navigation estimates. We introduce 3DSSDF (3D Sonar Reconstruction Using Signed Distance Functions), a new localization and 3D mapping algorithm based on signed distance functions, which is evaluated in simulation and on real data, in man-made and natural environments. Comparisons to reference trajectories and maps demonstrate that, in our tests, 3DSSDF efficiently corrects navigation drift and that trajectory and map accuracy is always below 1 m and below 1% of the distanced travelled, which can be sufficient for the safe inspection of natural or artificial underwater structures.

This paper examines the relevance of using catenary-based curves to model cables in underwater tethered robotic applications in order to take into account the influence of hydrodynamic damping. To this end, an augmented catenary-based model is introduced to deal with the dynamical effects of surge motion, sway motion or a combination of both on a cable. Experimental studies are carried out with eight cables of varying stiffness, weight and buoyancy. One end of the cable is fixed, while the other end is moved by the underwater robot. The obtained results help to determine which cables and which dynamics are compatible with a fair estimation of the cable shape through the proposed models.

This paper deals with the estimation of the shape of a catenary for a negatively buoyant cable, connecting a pair of underwater robots in a robot chain. The new estimation method proposed here is based on the calculation of local tangents thanks to the data acquired from inertial measurement units (IMUs), which are attached to the cable near its ends. This method is compared with a vision-based estimation method that was developed previously. Experiments are conducted, in the air and in a pool, using a motion capture system for ground truth. The results obtained show that the new method significantly improves the estimation of the catenary height. Furthermore, the identification of the cable shape is not affected by the limits of the camera's field of view and by the image projection, resulting in increased accuracy and range, without singularities.