SIAR: an autonomous ground robot for sewer inspection

D. Alejo1, C. Marques2, F. Caballero3, P. Alvito2 and L. Merino1

1School of Engineering, Universidad Pablo de Olavide, Crta. Utrera km 1,Seville, Spain. Email: {daletei,lmercab}@upo.es

2IDMind, Lisbon, Portugal. Email: {cmarques,palvito}@idmind.pt3Dpt. of System Engineering and Automation, University of Seville,

Camino de los Descubrimientos, s/n, Seville, Spain. Email: fcaballero@us.es

Resumen

This paper summarizes the latest advances of theEU Project SIAR-ECHORD++, whose main ob-jective is the design of a new robotic platform forinspecting visitable sewers. The SIAR robot aimsto determine the sewer serviceability, to identifycritical structural defects, to perform sewer moni-toring and eventually to take water or gas samplesof the environment. To this end, an autonomousIP67 ground robot equipped with RGB-D sensorsand with a powerful wireless communication sys-tem is being developed. It is able to perform 3Dstructure reconstruction in real-time that could beused to detect defects in the sewer structures. Thispaper presents the key aspects in the design of theplatform as well as preliminary experimental re-sults in real sewer systems.

Keywords: Autonomous ground robot, sewerinspection, 3D reconstruction, sensing, navigation

1 Introduction

Sewer inspections require many people to work inrisky and unhealthy conditions. Moreover, sew-ers are classified as confined spaces which requirespecial health and safety measures, in addition toother risks present like slippery sections, obsta-cles or biological risks from the potential contactwith wastewater. These features make the processof sewer inspection a risky and expensive processthat requires improvements urgently. Therefore,introducing a robotic solution in this process aimsat reducing the labour risks, improving the pre-cision of sewer inspections and optimizing sewercleaning resources of the city.

Autonomous sewer inspection by robots is a harshtask in many senses: the environment is very ag-gressive with a high level of humidity and poten-tial toxic gases; the robot should move in verynarrow spaces with almost no place for maneuver-ing; and communications are very restricted due tolack of direct line of sight (NLOS). In addition, therobot needs to carry a wide range of sensors notonly for self-localization and navigation, but also

to perform the inspections tasks: visual imagingwith artificial illumination, 3D scanning sensorsfor metric environment reconstruction to facili-tate impairment detection or devices for air/wastesampling. These sensors increase the weight of thesystem and also drain the power of the robot withthe corresponding impact in battery life and au-tonomy.

Payload, autonomy (in terms of battery life andtraversed distance) and harsh environment alto-gether conform a working framework in whichground robots seem to be the best solution [13].Additional options include the use of micro aerialvehicles (MAVs) based on multi-rotors, given theirsmall size and maneuverability. However, thereare limitations that need to be considered, as thelimited payload capacity that current systems of-fer, in order to carry the required sensors withoutcompromising the robot autonomy; even tetheredmulti-rotors might not have enough payload dueto the additional weight added by the power cable.In addition, to the best of our knowledge thereare no water resistant commercial MAVs in themarket, a key factor for a robust sewer inspectionrobot. On the other hand, submarine robots arediscarded because the water level into the sewagenetwork is expected to be low during inspectionand monitoring tasks and the inspection capabili-ties from inside the water are very limited. Thus,ground robots are the best choice if long-term andhigh maneuverability are required, as they can bebuilt waterproof and sensors of different size andweight can be installed onboard.

There are a wide variety of robotic platformsfor gallery inspection already in the market. Inparticular, the sewer inspection scene can be di-vided in two fields: pipe inspection performedby small robots which can fit inside pipes; andsewer inspection performed by medium to bigsized robots which move inside galleries. Pipeinspection can be purely remote controlled, e.g.,Alligator, Minigator, Multigator and Flexigatorwheeled robots from IBAK [2] or Geolyn’s trackedrobots [1], but it can be also autonomous, e.g.,Solo tracked robots from REDZone [6] or Makro’swheeled worm type robot [3]. In sewer inspection

is also possible to find teleoperated solutions, e.g.,PureRobotics’ Pipeline Inspection tracked robot[4], and autonomous solutions, e.g., ServiceR-oboter wheeled solution from Fraunhofer IFF [5].However, they have been designed in order to in-spect small pipes and sewers and cannot be usedinside the visitable sewers.

The SIAR (Sewer Inspection Autonomous Robot)solution seeks to solve the problem by the cre-ation of an autonomous robot, with the possibil-ity of control from a human operator in case ofneed or emergency. By using the proposed wire-less system, augmented by the deployment of self-powered wireless repeaters, it will be possible totransmit bidirectional data between robot and anexternal operator, allowing the operator to changethe mission in real time, instead of having to waitfor the end of the sewer exploration to identifyproblems on the sewer system. The SIAR sys-tem will go beyond existing solutions through theinclusion of some innovative features, while main-taining affordable costs: configurable locomotionsystem with interchangeable wheels and tracksmodules and variable length/width of the tractionsystem; reliable navigation system based on datafusion from low-cost commercial RGB-D cameras,IMU and encoders, performing accurate localiza-tion and navigation on the sewer system, insteadof using more complex and expensive sensors forthe same task; inspection system with easy ex-changeable sensor payload, allowing the use of therobot in different applications instead of the usu-ally set of sensors used only for sewer inspection,and the introduction of devices for air/waste sam-pling that is not possible to find in the commercialinspection robots.

The rest of the paper is structured as follows. FirstSection 2 describes the main hardware parts ofthe SIAR platform. Then, Section 3 describes themain parts of the system architecture integratedin SIAR. Section 4 describes the results obtainedin initial experiments performed in real scenarios.Finally, Section 5 points out the conclusions ob-tained from the early results and the challengesthat are still remaining.

2 SIAR platform

The SIAR project will develop a fully autonomousground robot able to navigate through the sewagesystem with a minimal human intervention andwith the possibility of manually controlling thevehicle or the sensor payload when required. Inthis section, the main components of the platformare described and discussed.

Figure 1: SIAR robotic platform

2.1 Robot frame

Figure 1 presents the current robotic platformused in real experimental scenarios. The roboticframe is made with IP67 enclosings in order toaccommodate for the hardest environmental con-ditions during sewer inspection. A six-wheeledground robot with independent traction has beendesigned and implemented by the company ID-Mind as part of this work. It is able to navigateover a wide range of floors and small obstacles,including steps of over 20 cm. The axis of the twocentral wheels is positioned below the other ones,and the centre of gravity of the robot is locatedover that axis, so that for turning the robot canbehave closely to a differential-drive robot. Thisconfiguration is very flexible and adapts very wellto the different scenarios the robot can find dur-ing routine inspections. While this is not the finalsolution for the problem, it allows to test the lo-comotion concept. It carries LiFePo batteries forbatteries and electronics, with an autonomy of 5hours.

2.2 Sensing systems

There are several kind of sensors that can pro-vide a robot with detailed measurements of theenvironment. These sensors include 2D LiDARsuch as Hokuyo, 2D tilting laser that can obtain3D measures, and 3D LiDAR sensors such as thevelodyne HDL-32E [7], stereo cameras and RGB-D cameras.

When analyzing these options, 2D laser can obtainprecise measures at tens of Hertzs, but only cansense distances confined in a determinate plane lo-cal to the robot. Therefore, it can be used to senseobstacles in the surroundings, but it would haveto be complemented if holes or obstacles on thefloor have to be detected, or in order to perform a3D scan of the environment. On the other hand,

Figure 2: Detail of the sensors and computing unitin the SIAR platform

tilted laser sensors could be employed to performhole detection and 3D scans, but they offer thedata at a medium rate (Hertzs). 3D LiDAR sen-sors can provide the robot with a detailed 3D dataof its surrounding usually at tens of Hertzs, butthey are very expensive (thousands of dollars) andheavy (usually more than one kilogram). Stereocameras would need a good illumination in orderto be able to detect matches between the two cam-eras, and then compute their disparity. This is notthe case when inspecting sewers.

Therefore, RGB-D cameras emerge as a very con-venient alternative for performing 3D scans of thesurroundings of the robot as they offer distancemeasures at high frequencies (30 Hz) even with-out the presence of illumination. Also they areinexpensive (around 150 Euro) when compared tothe other Radar and LiDAR alternatives.

2.2.1 Current solution

The current SIAR platform counts with 4 RGB-D cameras from Orbbec1 disposed in the front,rear, left and right parts of it as depicted in Figure2. The front and rear sensors are special RGB-Dcameras with extended range that make them suit-able for navigation purposes. Additionally, twolateral RGB-D cameras (left and right) are usedfor obtaining more precise measures of the struc-tures walls.

2.2.2 Proposed design

In the proposed design, the number of sensorswill increase to 5 sensors (see Figure 3). In thefront and rear parts there will be located two long-range RGB-D cameras (up to 8 meters) that willbe mainly used for navigation and obstacle avoid-ance, although they also will be used for 3D re-construction of the ground and the walls. Theremaining three sensors have been placed in orderto enhance the detection of possible structural de-fects at the ceiling and in the upper parts of the

1https://orbbec3d.com

Figure 3: Proposed disposition of the cameras inthe SIAR platform

Figure 4: Detail of the angular disposition of ceni-tal and lateral cameras for obtaining a continuouspoint cloud. Cenital camera (Camera H) is point-ing towards the ceiling, while lateral cameras arerotated 40 degrees in the x axis

walls. The vertical disposition of the last threesensors is detailed in Figure 4. Note that the theFOV of the sensors has taken into account in or-der to obtain a continuous point cloud of the envi-ronment. The sensors will be enclosed with IP67protection as well. A specific computer will bedevoted to the capture and managing of the datafrom the 5 cameras.

2.3 Communication systems

The design of a wireless communication systeminside the sewer system involves a great challengedue to the harsh environmental conditions. Infact, it is common to find 100% humidity condi-tion. Another major issue is the presence of obsta-cles, such as walls, pipes, garbage which would notallow LOS transmission between the robot and thebase. In these circumstances, it is well known thatsignals with lower frequency would have betterpenetration properties than the ones with higherfrequency.

In the proposed solution, the robot will be able tocommunicate with the base station by two inde-pendent data links as follows.

1. Primary link. The robot will be equipped

with a long range WiFi in order to pro-vide the computers onboard of the robot andthe comms package with WiFi connectivity2.They have an advertised range of 50km, thatwill likely drop to less than 1km in indoors en-vironments. This link will provide the robotwith a high bandwidth connection (up to54Mbps) that could be used for video stream-ing and sending additional data informationsuch as the generated 3D map of the environ-ment, localization to name a few.

2. Backup link. The robot and base stationwill also be equipped with Microhard P9003

equipments. This link is able to connecttwo devices separated up to 50-100km witha data rate of 236Kbps in outdoor environ-ments with LoS. However, a reduction to therange of less than 1 km is expected in indoors.This range could be extended by the use of adirectional antenna in one of the sides. Thislink will be used for reliable image transmis-sion at low rates and reliable command trans-mission for teleoperation purposes.

Moreover, communication without direct LOS willbe allowed by automatically deploying repeaterswhenever the signal quality of the link goes belowa predefined threshold level. In order to do that,the robotic platform will be augmented with a de-vice to deploy and recover such repeaters. Thealternative solution is the use of a tether, includ-ing power and communications, connected to therobot at all times. This scheme is employed bymany robotic systems for pipe inspection, but itlimits greatly the maneuverability, and thus theability of the robot to inspect the sewer. Theuse of multi-hop ad-hoc networks have been shown[12] as an potential solution in similar scenarios.

3 System architecture

The systems that control the behavior of the SIARrobot have been developed with the Robotic Op-erating System4(ROS) using the ros-indigo distri-bution under Ubuntu 14.04. Figure 5 depicts thearchitecture of the main modules present in thesystem:

1. IMU driver. This package filter the rawdata produced by the inexpensive IMU sensorArduimu v35.

2http://www.microhardcorp.com/nVIP2400.php3http://www.microhardcorp.com/P900.php4http://ros.org5https://code.google.com/archive/p/ardu-imu/

Figure 5: Software architecture

2. MultiCamera driver. This package ex-tends the functionality of openni2 camera6

and openni2 launch7 packages. It providesthe user with a utility for generating launchfiles that sequentially activate each camera.Each camera can be configured with its ownsetup, i.e. changing the image rate, its reso-lution and many more.

3. Enhanced odometry. This package pro-vides enhanced odometry estimates by fus-ing IMU and encoders measures with visualodometry estimations [11]. The use of visu-ally enhanced odometry is very relevant inthese scenarios, where slippage is common.In this way, the SIAR platform is able to pre-cisely and robustly estimate the relative dis-placements. A good odometry estimation isnecessary for obtaining precise 3D maps ofthe environment[8].

4. Localization. These precise odometry esti-mations are used by this module in order toestimate the global position of the platform.This block uses prior information of the sewernetwork (localization of manholes, inlets, toname a few, available from a GIS) in order tocorrect the drift which is accumulated in theodometry estimation.

5. Local 3d mapping. This package gets theenhanced odometry and the precise localiza-tion outputs and uses them to integrate themeasurements from the different RGB-D sen-sors disposed over the SIAR robot. Thiswould allow the operator to have a precise 3Dlocal or global reconstructions of the sewer.

6. Navigation. The SIAR robot will be com-manded in three different operating modes.First, it can be purely teleoperated from thebase station. Then, an assisted teleoperationmethod will be developed in order to makethe robot automatically navigate through thecenter of the sewer, avoiding falling into holes,

6http://wiki.ros.org/openni2 camera7http://wiki.ros.org/openni2 launch

etc, while the operator command the velocityof the inspection. To this end, this modulehas to get a partial 3D reconstruction of theenvironment in order to detect the safe navi-gation areas where the robot can go through.Finally, a fully autonomous operating modewill use optimal kinodynamic sampling-basedplanners such as [10][9] to evaluate blockingconfigurations. This operating mode will fur-ther reduce the operator’s workload, as com-plete inspection plans could be loaded to theplatform, that will execute it automatically.Moreover, it would be crucial in case wherethe communication was lost. In this way, theplatform can safely perform an automatic re-turn home procedure.

7. Map analysis. This module provides thehigh level information required for sewer in-spection. It receives the local 3D maps andanalyzes them to extract sewer elements, es-timate the serviceability and inspect criticaldefects. Furthermore, the sewer network ele-ments like manholes and inlets, will be usedby the localization module for global localiza-tion.

8. SIAR driver. Software that interfaces withthe hardware board of the robot, and offersa standard ROS commands and services foreasy integration of the robot with the restof the system. This module will allow theoperator to command actions to the SIARwhich are not directly included in the navi-gation package, such as taking air or watermeasures and deploying repeaters.

9. Control Station. This module will sendan alert to the operator when critical condi-tions occur. These conditions can include au-tomatic detection of structural defects, badstate of the radio links, low battery indica-tor, the robot has lost traction and should berecovered, among others. It will also displaythe localization of the robot and the imagesfrom the onboard cameras in real-time.

4 Experiments

In this section, initial experimental results are de-scribed. In these experiments, the robot, in itscurrent state, was deployed in part of the sewersystem in Barcelona. The experiments were car-ried out in consecutive days on 2016, June 7-8.Each experiment lasted for three hours approxi-mately. These initial were aimed at checking thebasic capabilities of the platform. In the first day,a mobility test was carried out. The second day in-cluded a teleoperation test and an autonomy test.

Figure 6: SIAR robot navigating in the sewers ofthe Passeig of Sant Joan

Figure 7: SIAR robot navigating in the sewers ofValencia street

4.1 Scenario

The particular location of the experiment consistsof the sewers in Passeig Sant Joan, Barcelona (seeFigure 6). This first part of scenario is a specialpart of the sewer which is open to guided visits.Therefore, it is wider than usual and is providedwith an illumination system. However, the SIARplatform has also to be designed to travel insideregular sewers such as the depicted in Figure 7.These types of sewers are much narrower, are notilluminated, and present noticeable irregularitiesin their structure, which make the navigation insuch scenarios challenging.

Figure 8 depicts the sections of the different typesof sewers that have to be visited by the platform.The first section corresponds with the Passeig ofSant Joan. Then, the other sections are the mostcommon sections present in the regular sewers.Note that the width of the SIAR platform hadto be carefully tuned so the platform can navigatein the sides of the sewers of the Passeig of SantJoan, while being also capable of navigating overthe gully (one wheel at each side) of the other sew-ers. A map with the total travel to be carried outcan be found in Figure 9.

Figure 8: Sections of the sewers to be visited bythe SIAR platform

Figure 9: Total travel carried out by the SIARplatform

4.2 Mobility and autonomy results

The platform has been able to continuously oper-ate for 6 hours without battery recharges in theconsidered scenario, with a total traveled distanceof almost 2 km.

In each experiment the start location was the en-try of the sewers, marked by a red arrow in Fig-ure 9. The first mission was a mobility test inwhich the SIAR platform was directly teleoper-ated behind the robot at a close distance. In thisexperiment, the robot was able to navigate to thefurthest location marked in a green arrow.

In the autonomy test, the robot was commandedto travel the sewer at the Passeig of Sant Joanfor a one-way distance that exceeded 200m. TheSIAR platform was able to perform more than fourtravels, thus covering almost 1 km of total traveleddistance in this test. The test was carried outpartly teleoperated from the base station (one ofthe ways) and the rest of the time was directlyoperated.

4.3 Communication and teleoperationresults

One of the main objectives of the experiment wasto check the communication systems between thebase station and the robot. In the mobility test,the base station received a video link of the RGB-D cameras without interruptions with low delays(less than 0.2s). Communication without LOS

Figure 10: 3D local map reconstruction usingRGBD data.

was achieved thanks to the manual deploymentof a repeater just in the corner of the travel, thislocation is marked in purple in Figure 9.

Moreover, this video link was used in the experi-ments of the following day in order to teleoperatethe robot from the base station. In the teleopera-tion experiments, the robot reached a distance ofroughly 50m without any assistance. Then, theback-up link in which the commands were sentwas broken and therefore the robot was directlyoperated back to the Base Station. This bad per-formance of the 900MHz had not been detected inexperiments outside the sewer, in which its cover-age was greater than the 2.4 WiFi link.

Finally, the platform was teleoperated in one ofthe ways in the autonomy test without experienc-ing any difficulties or communication issues.

4.4 3D reconstruction results

The systems described in Section 3 have been usedto produce a detailed 3D reconstruction of thesewer system in real-time. Figure 10 representsa snapshot of the obtained 3D model along withthe actual images that were get from the frontcamera. Note that the resolution of the recon-struction could allow the operator to easily detectimperfections in the structure of the sewer.

5 Conclusions

The paper has discussed the main design decisionsfor the development of a sewer inspection robotfor big city sewers. The paper describes brieflyan initial platform used for tests, and the commu-nication and sensing systems. Cost-effectivenessis one of the main issues to be considered. Thepaper also depicts the architecture of the system.

Furthermore, the paper presents preliminar re-sults obtained in real sewers in tests related toautonomy, communications and mapping. Theseexperiments illustrate that the decisions made go

in the good direction.

As future work, the final design of the robotic plat-form and sensor payload will be pursued. Newfunctionalities will be developed and tested in thenext phases, including assisted teleoperation andnavigation autonomy modes, and enhanced per-ception capabilities to support the monitoring ofthe sewers.

Agradecimientos

This work has been developed under the Euro-pean project Echord++: European CoordinationHub for Robotics Development++ (FP7-601116)inside the challenge “Utility infrastructures andcondition monitoring for sewer network. robotsfor the inspection and the clearance of the sewernetwork in cities”.

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