Volume 4, Issue 4 - Special Issue on Maritime Robotics

Navigation systems of autonomous vehicles often exploit range measurement information that may be affected by outliers. In marine application the presence of outliers in sonar bathymetry, for instance, can be particularly severe due to multipath phenomena in the acoustic propagation. This paper describes a possible approach to process range measurements highly contaminated by outliers. The proposed solution builds on a robust parameter identification algorithm minimizing a nonlinear cost function that exploits the mathematical properties of Gibbs entropy. Numerical examples on simulated data are provided to illustrate the method and its performance. The use of simulated data allows to vary the amount of noise and outliers contamination while knowing the ground truth values of the parameters to be identified. For the sake of experimental validation, the method is also applied to third party (publicly available) upward looking sonar ice draft data collected by submarines in the Arctic Ocean.

The survey of waterbodies or underwater installations is a challenging task. To reduce the danger for divers, Autonomous Underwater Vehicles (AUVs) can be deployed. These requires a high manoeuvrability and agility in order to provide access in hard-to-reach areas. Smart-E is an omnidirectional AUV designed and developed at the Institute of Computer Engineering of the University of Luebeck. The drive is realized by the minimal configuration of three thrusters that are arranged at 120º to each other. To achieve omnidirectional movement in the 3D space, each motor pivots through 180º around its radial axis with the aid of a servo motor. This leads to a manoeuvrability of six degrees of freedom (DOF). Smart-E is equipped with various sensors like a pressure and temperature sensor, a 360º scanning sonar, an IMU-AHRS system and a tilt camera unit at the bottom. Besides the autonomous behaviors, the main challenge is to control all six DOF of the AUV to achieve a smooth and controllable omnidirectional underwater movement even in rough environments.

We present a seabed profile estimation and following method for close proximity inspection of 3D underwater structures using autonomous underwater vehicles (AUVs). The presented method is used to determine a path allowing the AUV to pass its sensors over all points of the target structure, which is known as coverage path planning. Our profile following method goes beyond traditional seabed following at a safe altitude and exploits hovering capabilities of recent AUV developments. A range sonar is used to incrementally construct a local probabilistic map representation of the environment and estimates of the local profile are obtained via linear regression. Two behavior-based controllers use these estimates to perform horizontal and vertical profile following. We build upon these tools to address coverage path planning for 3D underwater structures using a (potentially inaccurate) prior map and following cross-section profiles of the target structure. The feasibility of the proposed method is demonstrated using the GIRONA 500 AUV both in simulation using synthetic and real-world bathymetric data and in pool trials.

An algorithm for distributed exploration in 3D is presented which always keeps the robots within communication range of each other. The method is based on a greedy optimization strategy that uses a heuristic utility function. This makes it computationally very efficient but it can also lead to local minimums; but related deadlocks can be easily detected during the exploration process and there is an efficient strategy to recover from them. The exploration algorithm is integrated into a complete control infrastructure for Autonomous Underwater Vehicles (AUV) containing sensors, mapping, navigation, and control of actuators. The algorithm is tested in a high fidelity simulator which takes into account the dynamics of the robot, and simulates the required sensors. The effect of the communication range and the number of robots on the algorithm is investigated.

This paper proposes an interval based approach for localizing a group of underwater robots with unsynchronized clocks. We use sonar communication and consider that the travel time of the sonar waves cannot be neglected, e.g. when the robots are fast and far-spaced. Therefore we cannot suppose that we measure a true distance between robots at the same time, but between robots at di􀉼erent times. Moreover, as the clocks of the robots are unsynchronized, the emitting and receiving times of the sonar waves are uncertain. To solve this problem, we cast the state equations of our robots as a constraint satisfaction problem and consider the sonar measurements as intertemporal constraints on uncertain times. We introduce the notion of interval of function to encompass the robots trajectory and clock with their uncertainty. We then use interval propagation to successively contract these intervals around the true position and clock of the robots. Several test cases are provided, with both simulated and experimental results.