Hordur Kristinn Heidarsson

USC CINAPS Builds Bridges

More than 70% of our earth is covered by water, yet we have explored less than 5% of the aquatic environment. Aquatic robots, such as autonomous underwater vehicles (AUVs), and their supporting infrastructure play a major role in the collection of oceanographic data. To make new discoveries and improve our overall understanding of the ocean, scientists must make use of these platforms by implementing effective monitoring and sampling techniques to study ocean upwelling, tidal mixing, and other ocean processes. Effective observation and continual monitoring of a dynamic system as complex as the ocean cannot be done with one instrument in a fixed location. A more practical approach is to deploy a collection of static and mobile sensors, where the information gleaned from the acquired data is distributed across the network. Additionally, orchestrating a multisensor, long-term deployment with a high volume of distributed data involves a robust, rapid, and cost-effective communication network. Connecting all of these components, which form an aquatic robotic system, in synchronous operation can greatly assist the scientists in improving our overall understanding of the complex ocean environment.

Obstacle detection and avoidance for an Autonomous Surface Vehicle using a profiling sonar

We present an experimental study of a mechanically scanned profiling sonar for Autonomous Surface Vehicle (ASV) obstacle detection and avoidance. We extract potential obstacles from echo returns and suggest a scanning strategy for sonar in this application. We demonstrate with simulations (driven by data collected in the field) the potential for an ASV to rely solely on sonar data to navigate and avoid obstacles in a lake and harbor environment.

Obstacle detection from overhead imagery using self-supervised learning for Autonomous Surface Vehicles

We describe a technique for an Autonomous Surface Vehicle (ASV) to learn an obstacle map by classifying overhead imagery. Classification labels are supplied by a front-facing sonar, mounted under the water line on the ASV. We use aerial imagery from two online sources for each of two water bodies (a small lake and a harbor) and train classifiers using features generated from each image source separately, followed by combining their output. Data collected using a sonar mounted on the ASV were used to generate the labels in the experimental study. The results show that we are able to generate accurate obstacle maps well-suited for ASV navigation.

Cooperative control of autonomous surface vehicles for oil skimming and cleanup

Oil skimmers towed by two vehicles have been widely used for skimming of oil on the water surface. In this paper, we address the cooperative control of two autonomous surface vehicles for oil skimming and cleanings. We model the skimmer as a flexible, floating rope of constant length as well as discrete segmented model. We derive the equations governing the rope dynamics from first principles and demonstrate their application through simulations. We have performed field experiments with two autonomous surface vehicles that substantiate the proposed model and provides estimates of constants underlying the model. We propose a method for controlling the shape of the rope, and derive the conditions that maximize skimming efficiency.

Multi-Robot Collaboration with Range-Limited Communication: Experiments with Two Underactuated ASVs

We present a collaborative team of two under-actuated autonomous surface vessels (ASVs) that performs a cooperative navigation task while satisfying a communication constraint. Our approach is based on the use of a hierarchical control structure where a supervisory module commands each vessel to perform prioritized elementary tasks, a behavior-based controller generates motion directives to achieve the assigned tasks, and a maneuvering controller generates the actuator commands to follow the motion directives. The control technique has been tested in a mission where a set of target locations spread across a planar environment has to be visited once by either of the two ASVs while maintaining a relative separation less than a given maximum distance (to guarantee inter-ASV wireless communication). Experiments were carried out in the field with a team of two ASVs visiting 22 locations on a lake surface (approximately 30000m 2) with static obstacles. Results show a 30% improvement in mission time over the single-robot case.

A Communication Framework for Cost-effective Operation of AUVs in Coastal Regions

Autonomous Underwater Vehicles (AUVs) are revolutionizing oceanography. Most high-endurance and long-range AUVs rely on satellite phones as their primary communications interface during missions for data/command telemetry due to its global coverage. Satellite phone (e.g., Iridium) expenses can make up a significant portion of an AUV’s operating budget during long missions. Slocum gliders are a type of AUV that provide unprecedented longevity in scientific missions for data collection. Here we describe a minimally-intrusive modification to the existing hardware and an accompanying software system that provides an alternative robust disruption-tolerant communications framework enabling cost-effective glider operation in coastal regions. Our framework is specifically designed to address multiple-AUV operations in a region covered by multiple networked base-stations equipped with radio modems. We provide a system overview and preliminary evaluation results from three field deployments using a glider.We believe that this framework can be extended to reduce operational costs for other AUVs during coastal operations.

A topological approach to using cables to separate and manipulate sets of objects

In this paper we study the problem of manipulating and transporting multiple objects on the plane using a cable attached at each end to a mobile robot. This problem is motivated by the use of boats with booms in skimming operations for cleaning oil spills or removing debris on the surface of the water. The goal in this paper is to automate the task of separating the objects of interest from a collection of objects by manipulating them with cables that are actuated only at the ends, and then transporting them to specified destinations. Because the cable is flexible, the shape of the cable must be explicitly modeled in the problem. Further, the robots must cooperatively plan motions to achieve the required cable shape and gross position/orientation to separate the objects of interest and then transport them as specified. The theoretical foundation for the problem is derived from topological invariants, homology and homotopy. We first derive the necessary topological conditions for achieving the desired separation of objects. We then propose a distributed search-based planning technique for finding optimal robot trajectories for separation and transportation. We demonstrate the applicability of this method using a dynamic simulation platform with explicit models of the cable dynamics, the contact between the cable and one or more objects, and the surface drag on the cable and on the objects. We also demonstrate the working of the proposed algorithm on an experimental platform consisting of a system of two cooperating autonomous surface vessels and stationary/anchored objects.

Opportunistic localization of underwater robots using drifters and boats

The paper characterizes the localization performance of an Autonomous Underwater Vehicle (AUV) when it moves in environments where floating drifters or surface vessels are present and can be used for relative localization. In particular, we study how localization performance is affected by parameters e.g. AUV mobility, surface objects density, the available measurements (ranging and/or bearing) and their visibility range. We refer to known techniques for estimation performance evaluation and probabilistic mobility models, and we bring them together to provide a solid numerical analysis for the considered problem. We perform an extensive simulations in different scenarios, and, as a proof of concept, we show how an AUV, equipped with an upward looking sonar, can improve its localization estimate by detecting a surface vessel.

Experiments in autonomous navigation with an under-actuated surface vessel via the Null-Space based Behavioral control

This paper presents an autonomous navigation technique for an under-actuated surface vessel based on the use of a behavior-based technique, namely the Null-Space based Behavioral (NSB) control. The NSB control is used to generate motion directives for the vessel in order to sequentially visit various locations in the environment, while avoiding collisions with static obstacles. To work with under-actuated vessels, the NSB controller is coupled with a low-level maneuvering controller that generates the actuator forces to cause the vessel to follow the motion directives generated by the NSB. The overall control technique has been experimentally validated in the field with an autonomous under-actuated surface vessel navigating in a lake, avoiding collisions with small islands and a fountain.

Active Online Calibration of Multiple Sensors for Autonomous Surface Vessels

We present an approach to actively calibrate the exteroceptive sensors of an Autonomous Surface Vessel (ASV) autonomously. The approach consists of locating suitable calibration sites in the environment from aerial imagery, navigating to them, gathering calibration data and estimating the required parameters from data. We have conducted experiments using an ASV in a lake to validate our approach.