adaptable joystick control system for underwater remotely...

Adaptable Joystick Control System forUnderwater Remotely Operated Vehicles ?

Eirik Hexeberg Henriksen ∗,∗∗ Ingrid Schjølberg ∗

Tor Berge Gjersvik ∗∗

∗ Centre for Autonomous Marine Operations and Systems∗∗Department of Petroleum Engineering, and Applied Geophysics

Norwegian University of Science and Technology, NO-7491,Trondheim, Norway

(e-mail:[email protected], [email protected],[email protected])

Abstract: Current commercial remotely operated vehicles (ROVs) used for inspection, mainte-nance and repair tasks of subsea petroleum facilities are operated with a low level of automation.Precise and efficient operation of the vehicles is hard, and the vehicle operators need extensivetraining to operate these efficiently. A properly designed automation system has the potentialto lower the required skill and experience level for the operator, increase operation efficiencyand counteract operator fatigue. This paper uses theory from development of human centeredautomation (HCA) in the aviation industry to propose a new human centered control systemenabling shared control of ROVs.The control system is implemented in a simulator and evaluated qualitatively. The humancentered control system includes four modes of operation; position control, object of interestorbit control, autopilot mode, and waypoint guidance mode. The main contributions of thiswork are as follows: a human centered approach in ROV control system design, developmentof a reference velocity scaling for predictable position control, an adaptive joystick deadbandfunction, an orbit control mode using a super-ellipse as base shape. Finally, guidelines forpredictable control system behavior are suggested.

Keywords: Human Centered Design, Human Machine Interface, Remote Control, UnmannedUnderwater Vehicle, Subsea, IMR

1. INTRODUCTION

Most inspection, maintenance and repair (IMR) opera-tions on subsea petroleum extraction facilities are per-formed using remotely operated vehicles (ROV). Cur-rently there are over 5000 subsea Xmas Trees installedon the seafloor of the world’s oceans. All these need tobe inspected and maintained yearly by ROVs. These areunmanned underwater vehicles controlled from a surfacevessel through an umbilical cable. This class of vehicles hashad a rapid development curve from the 1970s, when theywere first introduced for work in the oil and gas industry.However commercial ROVs used today have not followedthe development of other industries when it comes to au-tomation (Offshore Engineer (2015)). ROVs are currentlyoperated in a direct control mode. The operator uses ajoystick to control forces produced by the ROV-propellers,and a master-arm is used for controlling the position ofthe manipulator arms (slave-arm). IMR operations oftenrequire at least two operators (ROV pilots). These pilotsneed extensible training to be able to control the ROVefficiently, and a persistent situational awareness is critical.

? This work is supported by the Research Council of Norway,Statoil and FMC Technologies through the project Next GenerationSubsea Inspection, Maintenance and Repair, 234108/E30. The workis associated with CoE AMOS, 223254.

Introducing more automation in the ROV control systemhas the potential to relieve the operator from the tedioustask of manual control during long operations. This willcounteract operator fatigue and make the operator workfaster with less training (Schjølberg and Utne, 2015).

The goal of the work is to introduce shared control forROVs performing IMR operations, making the operationsfaster, safer and easier.

Yoerger et al. (1986) introduce the idea of relating joystickcommand to different reference frames and use this topropose different control modes. The work showed thatperformance is improved with a closed loop control systemusing shared or supervisory control. This evaluation wasbased on simulation with a pilot in the loop. This veryearly work did not consider human performance, and theconclusion was based on the track following capabilities ofthe control system. Dukan and Sørensen (2012) focused onmethods for relating joystick commands to ROV motionsand references. Three different schemes were proposed andexperimentally tested. Two of the methods use a filteredjoystick command as a velocity reference, one is integratedto a position reference and one is used directly. The thirdmethod relates the filtered joystick command directly tothrust forces on the ROV. The control system switchesto position control when the velocity or thrust reference

Preprints, 10th IFAC Conference on Control Applications in Marine SystemsSeptember 13-16, 2016. Trondheim, Norway

Copyright © 2016 IFAC 167

is zero. This is to keep the vehicle in a fixed position.Candeloro et al. (2015) takes an alternative approachto ROV-control by using a head mounted display withinternal motion sensors to control an ROV.

This work develops a human in the loop (HITL) controlsystem to be used for subsea IMR tasks. An ROV controlsystem architecture for IMR operations is proposed. Thearchitecture is developed using theory from HCA origi-nating in the aviation industry. The different modes inthe architecture include concepts from previous research.To investigate the usability, the control system was imple-mented in a simulator and tested with an operator in theloop. This testing was done in a qualitative manner withfocus on user friendly operation of the ROV, and revealedweaknesses in the system. The presented work analysesthese weaknesses, and proposes solutions for making thesystem more user friendly and robust.

The contributions in the presented work are to bring intheory from HCA from the aviation industry to ROVcontrol system design. This is used as a basis for proposingdesign guidelines for the ROV control system. The theoryand guidelines form the fundament for a new ROV controlarchitecture with a higher level of automation than whatexists in current commercial ROVs. The control archi-tecture is novel and important as large cost savings areexpected due to increased efficiency in IMR operations.Operator friendliness has been an important aspect in thedesign, and has led to the following contributions:

• A velocity scaling function to avoid joystick wind-up• Adaptive joystick deadband for straight line manou-

vers• An orbit control mode for inspection of subsea equip-

ment with a rectangular footprint

This paper is organized as follows: Section 2 gives ashort synopsis of HCA, and HITL control systems. Section3 describes the different control modes and high levelarchitecture of the control system. The control modes arepresented in Section 4 and 5. Section 6 concludes the work.

2. GUIDELINES AND HUMAN IN THE LOOP

This section will give a synopsis of the concepts relevant forthis work. Starting with a short introduction to HCA, andthen an overview of the concept of having a human in thecontrol loop, and distinguishing this from an automatedfeedback loop.

2.1 Guidelines for Design and Implementation

Designers of new automation systems often have a ten-dency to be too technology centered, trying to automateevery part of the system (Norman, 1990; Sheridan, 2001).However, there are often tasks that are either too dif-ficult or too expensive to automate. A human operatoris therefore needed to monitor the system, to take overin case of an incident and to perform the tasks that arenot automated. A more thoughtful approach to functionallocation is the compensatory principle. In this approach,tasks are allocated to man or machine according to anassumption about who is best qualified to perform thetask. This method originates from Fitts list (Fitts, 1951),

which in spite of its age and criticism has persisted throughhistory (Winter and Dodou, 2014).

Both the technology centered approach and function allo-cation tend to lead to problems in the human-machine rela-tion, described as the ironies of automation in Bainbridge(1983). There is literature to be found on design principlesof HCA, especially in the aviation domain. However, whenit comes to functional design and implementation of aHITL motion control system there is a need for more tangi-ble guidelines. Billings (1996) and Atoyan et al. (2006) pro-vide guidelines for designing a HCA system. Such systemcan be viewed as a three piece system; the human operator,the automation system and the human-machine interface.HCA is a term often describing automation interactingwith humans, where the goal is to optimize the overallperformance of the system (Sheridan, 1995). This includeshandling of both automation and human errors. Sharedcontrol is a similar term that most often is used to describean automation system where the control is shared betweenan automation system and a human operator.

The presented work is focusing on the development of acontrol architecture supporting shared control for subseaIMR tasks. While many of the guidelines from the litera-ture are related to training of the operator, and design ofthe human machine interface, the following four guidelinesare addressing the ROV control system. These are pro-posed as the guidelines for designing the control system inthe presented work (Billings, 1996; Atoyan et al., 2006).

1) The automated systems must be predictable2) Provide the user with adaptable automation3) The automated systems must also monitor the human

operators4) The automated system must be comprehensible to

pilots

Guideline number two suggests that the operator canchange the level of automation during mission execution.This switch between control modes must be intuitive andeasy. To achieve this, the control system should be stableduring a switch between control modes (guideline 1). A setof more detailed guidelines for predictable control systembehavior during operation is proposed:

1a) The velocity and position references during switchingshould be continuous

1b) A command from the operator, should always lead toa vehicle response

1c) The same operator command should lead to similarresponse, despite of the current operating mode

1d) If a stop is commanded, the vehicle should stop asfast as possible, without reversing

2.2 Human in the Loop and Joystick Control

HITL control refers to the situation where a human ispresent in the control loop, fulfilling one or several controlfunctions. The classic (closed) control loop consists of acontroller and a process. The controller receives feedbackfrom the process, and controls the actuators to drive it tothe desired set-point. In ROV-control a human typicallytakes the place of the controller, and use video feedbackfrom the vehicle to control the thrusters on the vehicle.A block diagram for such control loop can be seen in

2016 IFAC CAMSSept 13-16, 2016. Trondheim, Norway

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Fig. 1. Human in the Loop in traditional ROV control

Figure 1. Many ROV manufacturers do however supplytheir vehicles with “auto-functions” for heading and depth.

In the traditional ROV control system, the operator usesvideo feedback to estimate the current position of theROV. This is denoted the perceived position. ROV opera-tions in the high-end range often use transponders to showthe ROV position in a chart-plotter. The operator usesthe joystick to command a thruster force output movingthe ROV towards the desired position. The precision ofthis control is very dependent on the skill of the operator;how well she manages to estimate the position based onvideo feedback, and how good her “internal model” ofthe dynamic response of the vehicle under actuation is.This internal model is one of the factors that distinguishesskilled operators. In the case of environmental loads suchas currents, the operator need to constantly account forthese.

Varying environmental forces are acting on the ROV, andits cable. Human perception of these forces are only possi-ble by coupling the motions observed in a video-image andapplied thrust with the pilots internal model of motion.This is a challenging task, and makes the performanceof direct control sub-optimal. This is a motivation forintroducing automation. An automated control loop willbe faster and more precise as a computer is capable ofreceiving and processing sensor feedback faster than ahuman. The human is however indispensable in missionplanning, and execution because of the cognitive abilitiesnecessary for replanning, equipment diagnostics and situa-tional awareness. The question is then how to best involvethe human in the control loop, while at the same timeutilizing automated control and navigation.

3. SYSTEM ARCHITECTURE

In the following an adaptable shared control system en-abling several control modes is presented. The overallarchitecture with four operating modes is illustrated inFigure 2. The different control modes are realized byswitching between control loops. References for the controlloops can be generated either by system, human, or acombination of these. The control system is described withrespect to a typical offshore inspection consisting of severalphases:

• Transit from A to B• Inspection of subsea equipment

In the transit phase a suitable control scheme willbe an autopilot, controlling the heading, velocity anddepth/altitude of the ROV. The reference from this con-troller can either come directly from the operator viathe joystick, or by an automated guidance system withpreprogrammed waypoints.

Fig. 2. Adaptable shared control system architecture en-abling different operating modes

The main objective of an inspection mission is video-camera based visual inspection. In this phase the orien-tation of the ROV is important, as the video camera mustbe facing the subsea equipment. Two different modes forinspection is proposed, position and orbit control. Both areusing a 4-DOF position controller. The controller is con-trolling north and east position, as well as depth/altitudeand heading. The difference between the modes is thatthe reference is given by the joystick in two different ways.In the first mode (position control) the output from thejoystick is interpreted as a velocity reference in the vehicleframe. This velocity reference is then fed into a positionreference filter to get the position. The other control modeis an orbit control mode. In this mode the joystick outputis mapped to a cylindrical-like coordinate system wherethe object of interest is placed at the origin. In this modethe ROV will always face towards the center of the objectof interest, while moving around it. The joystick is usedto control the radius of the orbit, the angle of observationand the depth.

The four control modes that are suggested are meantto extend the current control system of the ROV wherethe joystick motions are mapped directly to a thrustoutput on the ROV. It is important when designing ahuman centered control system that it is both easy for theoperator to engage the automatic control system, as well asto intervene and do corrections. In the proposed design theoperator should be able to easily switch between all controlmodes, according to guideline 2. It is important that thevehicle acts according to the operators anticipation duringa mode change. This is reflected in guideline 1a. Theproposed design is found as a block diagram in Figure 2.The dashed lines represent switch options.

3.1 Implementation Aspects

The control system proposed in this article is implementedand tested in a simulator using “perfect feedback”. In thesimulation the ROV moved in a 3D virtual world, and wascontrolled by an operator. The 3D world is shown in Figure6. The sensor-data used by the control algorithms are un-biased and without noise. This is however not the situationin a real subsea IMR operation. It is assumed that in a


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real scenario, the ROV will be equipped with a sensorsuite and navigation filters, together capable of estimatingthe velocity and position of the ROV without drift inthe estimates. Such drift would cause the ROV to driftcorrespondingly while stationkeeping. This would cause anunpredictable behavior where the operator would need tointervene in the automatic execution. The estimates do notneed to be globally corrected, as the operator is workingon the basis of camera feedback given in a local frame.

The system is comprised of a set of control and guidancealgorithms that individually are stable. Switching betweenthe modes are initiated by the human operator. Thisimplies that the switching happens relatively slowly. It istherefore assumed that the switching between modes doesnot introduce any unstable behavior.

4. TRANSIT MODES

The autopilot and waypoint modes shown in Figure 2 areused when the ROV is in transit between work locations.These modes are controlling the vehicle while the oper-ator can rest and observe the operation. The automaticcontroller is taking care of the heading, forward speed, anddepth/altitude. When waypoint mode is used, the headingreference is made by the waypoint guidance system. Inthe autopilot mode the heading reference is controlled byusing the joystick, and the operator takes the role as aguidance system. Both modes use the autopilot controllerfor allocating thrust to the ROV. The waypoint controlloop is illustrated in green and the autopilot loop in blue inFigure 2. The autopilot controller is a PID-controller witha feed-forward velocity reference. The waypoint guidancescheme is a lookahead based line-of-sight steering law fromFossen (2011).

If the operator wants to step out of the waypoint mode, e.g.to take a closer look at something odd along the route, thecontroller saves the current position as a waypoint. Thisallows the operator to easily go back to the predefinedroute even after the aborting the execution. This feature ismeant to lower the threshold for the operator to intervenein the automatic execution. This adaptable behavior isaccording to guideline 2.

5. POSITIONING MODES

During a subsea inspection the operator control objectiveis position control, and the position mode or orbit modein Figure 2 is used. External disturbances are acting onthe ROV so continuous control action is needed to keepthe ROV at the desired position. The proposed positioncontroller enables the operator to change position andorientation using the Joystick, and let the control systemhandle the force allocation to keep the vehicle on position.

The designed position control system will account forexternal disturbances and map joystick inputs to ROVmovements in an intuitive way. Both in position and orbitmode the joystick deflection is interpreted as a desiredvelocity. This velocity is then transformed and integratedto a position reference. In the position mode the velocity isin the vehicle reference frame and is directly transformedinto the global reference frame (red control loop in Figure2). In the orbit mode the velocity is given in a cylindrical

like coordinate system where the center of the orbit isplaced in the origin (yellow loop in Figure 2). In orderto make the position and velocity references continuousduring a switch between modes, the mode that are beingswitched to is initialized using the position, and velocityfrom the current mode.

5.1 Position mode

A nonlinear PID-controller with a feed forward referenceis applied for position control. This is a well knownand relatively simple controller. This corresponds withguideline 4, calling for a comprehensible control system.For position reference generation the approach proposedby Dukan and Sørensen (2012) is used. This is a low-passfilter cascaded with a mass, damper and spring systemapplied to the joystick output. The filter output is asmooth position reference as well as a reference velocityused as a feed-forward to the position controller.

5.2 Orbit Control Mode

The orbit control mode enables the operator to circlearound an object of interest during an inspection. Thismaneuver is difficult to perform using manual control be-cause it changes the heading and position simultaneously.The idea of referencing joystick commands to a coordi-nate system using cylindrical coordinates is described inYoerger et al. (1986). Simulator testing revealed that acylindrical orbit was very handy when inspecting smallobjects (approximated by points), or larger objects with acircular base. However, for the offshore inspection scenario,most objects are quite large and rectangular in shape. Thismade the circular orbit unpractical as the distance to theobject change a lot during one lap. To adapt the orbitfor rectangular objects, it is proposed to change the baseshape from a circle to a super-ellipse. The difference indistance between path and object can be seen in Figure 3.

The standard parametrization of the super-ellipse resultsin an along-path velocity that is varying considerably.This makes it unsuitable to be used as a path. A newparametrization that solves this problem and results inconstant along-path velocity is proposed. This is done tomake the behavior more predictable (guideline 1).

The geometric shape of the super-ellipse is documentedin Weisstein (2016). This base shape has several shapingparameters, making it possible to generate a suitable pathfor the ROV to orbit around a subsea structure.

The super-ellipse shape is can be described by the follow-ing equations:

x(φ) = rA cos2/s(φ) (1a)

y(φ) = rB sin2/s(φ) (1b)

Where A, and B scale the shape along the x-, or y-axis,while r sets the size of the shape. φ is the control parame-ter. The parameter s is sometimes called the squarenessparameter and for s > 2 it controls the squareness ofthe shape. s = 1 produces a diamond shape, while s = 2produces an ellipse, or a circle if A = B. Using this baseshape will in other words give the possibility to adapt theorbit path to a lot of different shaped equipment. The baseshape can be rotated by using a 2D rotation matrix, and


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-4 -2 0 2 4 6

East [m]

-4

-3

-2

-1

0

1

2

3

4

5

6

Nort

h [m

]

Structure Outline

Circular Orbit

Superellipse Orbit

Fig. 3. Circular and Super-ellipse path around a rectangu-lar subsea structure

placed in the North-East plane by adding the coordinatesof the desired origin of the shape.

The r parameter is controlled in real-time by the opera-tor by pushing the joystick forwards or backwards. Thiscorresponds to moving closer or away from the structure,or moving the ROV forward and backward. When thejoystick is moved sideways, the vehicle will move alongthe structure following the path.

When using a cylinder as a base shape it was practicalto control this motion along the path by using the angleparameter φ. For a cylinder the relation between one stepalong the path was proportional to one angle step. For thesuper-ellipse however, this does not hold as the along-pathvelocity is dependent on φ. A velocity unproportional tojoystick input makes it very hard to control the vehicle.

The proposed solution is to map the joystick y-axis tothe along-path speed and then calculate the a new angleparameter based on this speed. This was done by substi-tuting the variable θ for ω in (1). The new path variableis calculated numerically using the following relations:

s′ =√x′(φ)2 + y′(φ)2 (2)

ω =

∫ t

0

Ud

s′dt (3)

where Ud is the commanded along-path velocity, x′(φ) andy′(φ) is defined in (1). The denominator in (3) is infinityat the x-, and y-axis of the shape, causing the fractionto go towards zero. This is solved in the implementationby saturating the denominator at a high threshold. Thismay cause the along-path velocity to be slightly higher atone timestep when crossing the x- and y-axis. Simulatortesting shows that this is not noticeable by the operator.

5.3 Joystick Wind-up

Testing revealed that in presence of currents the vehiclemay move slower than the filter reference. This may behard for the operator to notice, and may cause her to losecontrol over the vehicle. We named this problem joystickwind-up because of its similarities to integrator wind-up.

The reference filter is tuned so the maximum referencevelocity is slightly less than the ROV maximum velocity.

Time [s]

0 5 10 15 20 25 30 35 40 45

Positio

n e

rror

[m]

0

0.5

1

1.5

2

2.5

3

3.5

4

No Velocity scaling

Velocity scaling

Fig. 4. Position error with, and without velocity scalingduring a move towards the current

However, the reference filter does not take into accountcurrent forces. When the vehicle is travelling counter-current, the vehicle will lag behind the joystick generatedreference. This is because the ROV can not sustain thespeed set by the reference filter. If the vehicle is far fromthe setpoint this might cause confusion for the operator ashe/she does not get the expected feedback when movingthe joystick. The controller is chasing a position far awayfrom the vehicle and the vehicle will move in this directionat maximum possible speed, no matter if the operatorchanges the setpoint slightly. This is the same problemthat can lead to integral wind-up in PID-controllers.

In order to mitigate this issue, a lag based velocity scalingfunction is proposed for the reference filter. The idea isto multiply the reference speed with a scaling-factor whena lag is detected. The scaling parameter is calculated andapplied in the global frame, as the current-forces are actingin this frame. The scaling factor, S is calculated as follows:

Si =

1 if |ηdi − ηi| ≤ 1m

0.5

|ηdi − ηi|if ‖ηdi − ηi| > d

(4)

d is the lag treshold and S = Diag(S1, S2, S3, 1, 1, 1) as weonly apply scaling to the translational degrees of freedom.Figure 4 shows how the velocity scaling ensures that theposition error stays within a reasonable bound, making thevehicle controllable by the joystick, following guideline 1b.

5.4 Adaptive Deadband

When the operator attempts to move the vehicle at highvelocity and along a straight line using the joystick, it ishard to keep the vehicle moving along the straight line.The explanation is that when making a somewhat coarsemovement in forward direction to obtain a high speed,it is hard to avoid small movements in the transversedirections. To counteract such unintended commands it ispossible to introduce a deadband on the joystick output.A regular deadband however tend to remove precision forsmall deflections of the joystick. To keep precision andcounteract unintended motions in high speed an adaptivedeadband is proposed. This deadband, D is calculated as:


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D = k

6∑i=1

ηjsi (5)

where k is a tunable parameter controlling the size of theadaptive deadband envelope. The deadband is applied tothe joystick output as follows:

ηjsi =

{0 if ηi < D

ηjsi if ηi ≥ D(6)

When the deadband is applied to the joystick outputbefore it enters the reference filter it is significantly easierto make a straight line reference for the ROV at highspeeds. Figure 5 shows two test-runs where the operatorwants the ROV to move at high speed in a straight line.The figure shows a clear improvement in the horizontalplane, but also applies to a path in the vertical direction.

East

-6 -4 -2 0 2 4 6

No

rth

-5

-4

-3

-2

-1

With Adaptive deadband

No Deadband

Fig. 5. Position in the North-East plane during a straightline move with, and without adaptive deadband

6. CONCLUSIONS

Transit and position control modes for an ROV in IMRoperation are described in the previous sections. A con-trol system architecture is designed to enable adaptableshared control, allowing to switch between several modesof operation. The modes are designed to make the jobfor the human operator easier during an IMR operation.Less operator attention and effort is required as the ROVcontroller handles the external disturbances, as well asaiding in path following. For instance, the orbit controlmode allows the operators to automatically observe thesubsea equipment from all angles. The control systemallows the operator to focus on the actual work, such asobserving, or controlling the ROV tools or arms.

The architecture including four control modes is tested in asimulation environment, using the flexibility of the controlarchitecture to switch between the modes. The system isstill at a testing and development stage, but a qualitativereview has proved it easy to operate, even without train-ing. Topics for further work will include implementationof a more refined human machine interface, automatedcollision avoidance and other operator aid functionalityfor IMR operations. The system will be further verified bylaboratory experiments.

Guidelines for design of human centered automation foraviation was used in the design phase. The guidelines sug-gested that the system should include adaptable automa-tion and that it should be predictable and comprehensivefor the human operators. The last guideline suggested thatthe automation system should also monitor the human toavoid errors. Guidelines to ensure predictable behavior ofthe system are proposed. The goal of the work is to in-troduce human friendly automation for ROVs performing

Fig. 6. Operators view during testing of control system

IMR operations, making the operations faster, safer andeasier. In a future scenario we might see highly automatedvehicles remotely operated from shore performing IMRoperations subsea.

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