Autonomous subsea intervention (SEAVENTION)

This paper presents the main results and latest developments in a 4-year project called autonomous subsea intervention (SEAVENTION). In the project we have developed new methods for autonomous inspection, maintenance and repair (IMR) in subsea oil and gas operations with Unmanned Underwater Vehicles (UUVs). The results are also relevant for offshore wind, aquaculture and other industries. We discuss the trends and status for UUV-based IMR in the oil and gas industry and provide an overview of the state of the art in intervention with UUVs. We also present a 3-level taxonomy for UUV autonomy: mission-level, task-level and vehicle-level. To achieve robust 6D underwater pose estimation of objects for UUV intervention, we have developed marker-less approaches with input from 2D and 3D cameras, as well as marker-based approaches with associated uncertainty. We have carried out experiments with varying turbidity to evaluate full 6D pose estimates in challenging conditions. We have also devised a sensor autocalibration method for UUV localization. For intervention, we have developed methods for autonomous underwater grasping and a novel vision-based distance estimator. For high-level task planning, we have evaluated two frameworks for automated planning and acting (AI planning). We have implemented AI planning for subsea inspection scenarios which have been analyzed and formulated in collaboration with the industry partners. One of the frameworks, called T-REX demonstrates a reactive behavior to the dynamic and potentially uncertain nature of subsea operations. We have also presented an architecture for comparing and choosing between mission plans when new mission goals are introduced.publishedVersio

Coordinated Control with Obstacle Avoidance for Robot Manipulators

This thesis addresses the problem of robot synchronization with obstacle avoidance. While these two fields have been studied extensively on their own, they have not yet been considered together as one problem. This thesis is divided roughly into four parts which are to some extent self contained. The theory is presented in a narrative that culminates with the stability proof of the proposed controller. Examples and figures are used in order to keep the material manageable and readable. The introductory part of the thesis consists of chapters 1 and 2. We present the notation and some mathematical background which is necessary for the theoretical analysis. We go on to review the diversity of ways in which one may approach this problem from a control design standpoint. We derive the robot dynamical model in chapter 3 as well as solve other modeling specific problems. This chapter is of little theoretical interest, but is needed to implement a simulator on which we may test our controller. This chapter contains no new contributions but can be read as a guide to robot modeling. The first contributions in this thesis are found in chapter 4 where we propose a real time implementable solution for solving the shortest distance estimation problem. It is important to know the distance to an obstacle in order to avoid it. The solution is a dynamic implementation of a steepest descent optimization scheme which is suitable to run on-line. Chapter 5 is an introduction to the involved control design found in chapter 6. We review results from obstacle avoidance literature and argue for our choice of using the task space control design method. The main contribution of this thesis is found in chapter 6. A controller is developed and is shown to produce a stable closed loop system. We first develop a controller considering only collision for the end effector, and then we extend this to work with full robot collision. The response of the robot is such that it will track a reference trajectory whenever it is locally possible. When one cannot track the reference trajectory because of obstacles hindering the movement, then the trajectory is tracked in all directions in which the robot can move freely. The controller is simple and elegant, and does not rely on heuristics common in traditional solutions to obstacle avoidance control

Stability Analysis of a Hierarchical Architecture for Discrete-Time Sensor-based Control of Robotic Systems

The stability of discrete time kinematic sensor-based control of robots is investigated in this paper. A hierarchical inner-loop/outer-loop control architecture common for a generic robotic system is considered. The inner loop is composed of a servo-level joint controller and higher level kinematic feedback is performed in the outer loop. Stability results derived in this paper are of interest in several applications including visual servoing problems, redundancy control, and coordination/synchronization problems. The stability of the overall system is investigated taking into account input/output delays and the inner loop dynamics. A necessary and sufficient condition that the gain of the outer feedback loop has to satisfy to ensure local stability is derived. Experiments on a Kuka K-R16 manipulator have been performed in order to validate the theoretical findings on a real robotic system and show their practical relevance.publishedVersio

Snake Robots for Space Applications(SAROS)

This report explores relevant concepts for use of snake robots in Space, specifically for use onboard the International Space Station, for exploration of Moon lava tubes and for exploration of low-gravity bodies such as asteroids, comets and small moons. Key abilities that snake robots need to have in order to carry out the aforementioned operations, as well as challenges related to realizing such abilities are discussed. Oppdragsgiver: European Space Agency (ESA)publishedVersio

Deburring Using Robot Manipulators: A Review

Deburring of cast parts can be a very challenging task. Today, large burrs on large casting are mostly removed manually. Workers are exposed to hazardous working conditions through, among other things, high noise and vibration levels. Special purpose CNC-machines are available for deburring tasks, but they have a high investment cost that makes them unfit for high-mix low-volume processes. Deburring with robot manipulators are seen as a suitable and less expensive alternative, and have been in the focus of research topic for the last 50 years. Unfortunately, it has failed to move from research into industrial applications. One reason is the long system setup time that makes the cost of automatic deburring too high. This paper deals with the status and usage of robot manipulators in deburring applications with focus on solutions for cast parts. The deburring pipeline and its components are investigated. There is a special focus on the solutions that lead to a more flexible and automatic deburring system by using sensors such as laser, vision and force control. The solutions are evaluated with regards to the current challenges with robotic deburring and what needs to be improved for robotic deburring to become available for high-mix low-volume processes

SEAVENTION - Autonomous underwater intervention

submittedVersio

Stability Analysis of a Hierarchical Architecture for Discrete-Time Sensor-based Control of Robotic Systems

The stability of discrete time kinematic sensor-based control of robots is investigated in this paper. A hierarchical inner-loop/outer-loop control architecture common for a generic robotic system is considered. The inner loop is composed of a servo-level joint controller and higher level kinematic feedback is performed in the outer loop. Stability results derived in this paper are of interest in several applications including visual servoing problems, redundancy control, and coordination/synchronization problems. The stability of the overall system is investigated taking into account input/output delays and the inner loop dynamics. A necessary and sufficient condition that the gain of the outer feedback loop has to satisfy to ensure local stability is derived. Experiments on a Kuka K-R16 manipulator have been performed in order to validate the theoretical findings on a real robotic system and show their practical relevance

Autonomous Job Analysis: A Method for Design of Autonomous Marine Operations

-Increased use of autonomy is considered crucial for continued growth in maritime industries like oil- and gas, waterborne transport, and fisheries- and aquaculture. This article presents a method called Autonomous Job Analysis (AJA), which purpose is to guide the design of autonomous marine operations. AJA breaks down the operation, and focuses on autonomy early in the design phase. The method uses elements from Hierarchical Task Analysis (HTA), and the execution of the analysis is influenced by HAZard and OPerability (HAZOP) studies. The proposed method is illustrated through application on two different case studies: Inspection of mooring lines in a sea-based fish-farm, and imaging of plume extension caused by discharge from a waste water plant

Canvas as a design tool for autonomous operations: With application to net inspection of a sea based fish farm using an underwater vehicle

Several design methods and principles have been proposed in the literature in order to guide the design of autonomous operations. Putting the required efforts into learning and using the methods is a daunting task, and experiences have shown that the use of methods meant to the help the design process are often ignored. The reason could be that the design guidelines are too complex and contain information that is not relevant for the project at hand, and that there is no easy way to distinguish what is important from what is not. In this article, we propose a canvas as a tool to support the use of Autonomous Job Analysis (AJA). The authors have previously developed AJA as a structured method for designing an autonomous operation by breaking it down in to sub-operations in order to reveal challenges, needs and limitations regarding autonomous behavior. The canvas contains the categories of the AJA method on a single page - the canvas - and each category is supported with questions to be asked during the design procedure, as well as example answers. We will describe the AJA canvas in detail, and show how it can be applied to design an autonomous operation for inspection of the net of a sea based fish farm using an underwater vehicle.acceptedVersio