TOWARDS THE DEVELOPMENT OF A LOW-COST REMOTELY-PILOTED LAND MOBILE MAPPING SYSTEM

Transcription

1 TOWARDS THE DEVELOPENT OF A LOW-COST REOTELY-PILOTED LAND OBILE APPING SYSTE Julien Li-Chee-ing and Costas Armenakis Geomatis Engineering, GeoICT La Department of Earth and Spae Siene York University Toronto, Ontario 3J 1P3, Canada { julienli, armen ABSTRACT The aquisition of spatial data is a ritial operation in situations where onditions are unfavourale for manoperated mapping systems. Suh situations inlude monitoring onstrained environments, emergeny response, and firefighting. Low-ost unpiloted vehile platforms offer a great opportunity for developing moile mapping systems, enaling the automated olletion of spatial data in ritial environments. In this paper, an overview of a low-ost unmanned remotely piloted moile mapping platform and its onoard sensors are given, inluding system requirements, design onsideration and system omponents. This low-ost remote-piloted vehile platform is equipped with an onoard navigation system (, inertial measurement unit (IU), magnetometer), a digital amera, and a remote ontrol ommuniation system for rapid 3D data olletion. To support funtions suh as ommand, ontrol, monitoring of the moile mapping platform and sensor loation and 3D feature extration, a proposed approah for diret georeferening, sensor loalization, time synhronization and system aliration is presented. INTRODUCTION Unmanned vehiles (UV) were developed primarily for military appliation, ut reently a new generation of ivilian miro, mini and lose range UV started to e employed for time-ritial operations, suh as monitoring onstrained environments, emergeny response, and firefighting. The use of low-ost unmanned moile mapping systems (US) for mapping, monitoring and traking is at a very early stage of development, ut over reent years the geospatial information industry has signifiantly expanded in oth government and industry setors. As suh, the demand has inreased for fast and effiient tehniques for aquisition, proessing, and presentation of large quantities of geospatial data. The ultimate goal of the US is to provide metri and themati data aout the mapped features and ojets in the form of geo-produts, DE/DS and orthoimages, 3D models and video data. The fundamental step in generating this geospatial data is the transformation of data olleted y imaging and ranging sensors, suh digital ameras or Light Detetion and Ranging (LIDAR) laser sanners, from the loal ody platform frame to a mapping frame. This is the well-known proess of georeferening. Initially, georeferening was performed indiretly using image lok adjustment and ground ontrol points (GCPs) through photogrammetri triangulation (PT). Estalishing ground ontrol is an expensive, time-onsuming and hallenging task. Further, the PT proess is also time-onsuming, requires an experiened operator and is not well-suited for real-time appliations. Consequently, moile mapping systems (S) are eing developed to overome these drawaks y eliminating the use of ground ontrol. These systems are ommonly implemented on terrestrial vehiles, or aerial platforms, suh as heliopters or planes. For a detailed examination of moile mapping systems, see Li (1997). Current S have not gained muh popularity in the geomatis industry eause of their omplexity and high osts. This researh aims to develop a US that is user-friendliness and more importantly, low-ost, while ahieving omparale auraies to the aforementioned traditional survey tehniques. SYSTE REQUIREENTS This paper details the development of a US, using low-ost sensors on-oard a low-ost unmanned ground vehile platform. The S integrates navigation sensors, mapping sensors, logging omputer, and through proessing algorithms, the 3D positions of points are determined remotely. Navigation sensors, suh as and inertial measurement units (IU), determine the exterior orientation (position and attitude) of the mapping sensors; ASPRS 2010 Annual Conferene

2 this is known as diret georeferening. Imaging and ranging sensors determine the position of points external to the platform. The system eing developed is set to ahieve RS positioning auray in the range of 1/100 with respet to the given ontrol framework. The speified auray is required in all environments, inluding uran areas, where positioning is unreliale. This paper will detail the tasks required to satisfy this requirement. Firstly the seleted system hardware is desried, followed y methods of /IU/Camera integration and synhronization, the georeferening model is then developed, finally sensor and system aliration tehniques are desried. SYSTE DESIGN The US uses onoard navigation sensors to diretly determine the position of the vehile platform and the pose parameters of the imaging sensor. A proven solution is an integrated navigation system that integrates a Differential (D) and an Inertial Navigation System (INS). The navigation sensors are divided into two ategories: positioning sensors, and attitude sensors. Positioning Sensors will provide the position eause no other positioning tehnology offers the same auray and flexiility at the same ost. Further, is widely aepted in the surveying and mapping industry. Also, the reeiver outputs a preise lok signal (1 PPS) that an e used for synhronization of the system omponents. Ellum and El-Sheimy (2001) list several modes of operation that are potentially appliale to a low-ost S. The L1 arrier-phase Real-Time Kinemati (RTK) solution is the most appliale to a low-ost terrestrial S. Geodeti-grade reeivers with firmware supporting RTK- are very expensive ompared to general-purpose reeivers. This is one reason why RTK- is still not popular and is used only for limited appliation areas. Takasu (2009) onstruted a low-ost single-frequeny RTK- reeiver and otained m-level positioning auray. However, expensive dual-frequeny reeivers have an advantage of muh shorter time for amiguity resolution. With a single-frequeny reeiver, at least a few minutes are neessary to otain a first fixed solution. Attitude Sensors Ellum and El-Sheimy (2001) list possile sensors for attitude determination and provides the advantages and disadvantages of eah. A low-ost inertial measurement unit (IU) is the hosen attitude sensor eause, unlike the alternatives, it operates independently to provide a omplete navigation solution - position, veloity and attitude, thus it is ale to ridge outages. Further, the IU s a high data rate allows for preise interpolation etween fixes. The main soure of error in position omes from the errors in the determination of the azimuth. The high drift rate of the low-ost IU will not allow aurate azimuth determination without the use of azimuth updates from heading sensors. Thus, the US will integrate a magneti sensor into the system to provide the azimuth angle updates in the Kalman filter. A digital ompass an provide a relatively stale auray of up to ±0.5. agneti north does not oinide with geodeti north, thus magneti sensors require knowledge of the earth s magneti field. Highly aurate gloal and regional models of the earth s magneti field are freely availale. For a general introdution to digital ompasses, see Caruso (2000). apping Sensors It is shown in Li (1999) that with aurate aliration and at the ojet to amera distanes that the US will e used at (less than 30 m), mm level auraies in the determination of ojet spae oordinates are possile with a onsumer grade digital amera. Single Board Computer The US requires a powerful, ut flexile, entral proessing unit that is easily integrated and expanded for use with different sensors and vehile platforms. This emedded omputer gathers and proesses all the information from the reeiver, IU and other sensors. The Linuxstamp serves as the US proessor. It is an open soure proessor module ased on the AT91R9200 miroproessor. ASPRS 2010 Annual Conferene

3 Ground Control and Command Station The ontrol and ommand station (CCS) onsists of a laptop, a RF transeiver module and a ase station. The US ommuniates wirelessly to the CCS through a XBee-PRO 900 RF module. It sends raw oservations, omputed navigation solutions and other information, while reeiving L1 oservations to ompute the RTK solution. The XBee transeiver was hosen eause it has wide range (10 km), low lateny and high data rate (156 Kps). Alternatively, the ase station an e replaed with a network RTK (NRTK) server. In whih ase, US requires a radio modem to onnet to an NTRIP aster via Internet. In either ase the oservations will e in the RTC (version 2 or 3) data format. This method is more attrative eause it signifiantly redues the ost and the amount of equipment used, while inreasing the flexiility and effiieny of the US. Data Logging Part of the proessing is performed in real time, suh as image ompression and initial quality ontrol. However, real-time geoferening is not reliale in uran areas, due to frequent loss of lok to satellites. Thus most of the data will e stored for post-mission proessing. SYSTE CONFIGURATION The four sensors that will e used in the US are a NovAtel OEStar reeiver, an ADIS16364 IU from Analog Devies In., a KVH Azimuth 1000 digital ompass, and a Kodak Digital Siene DC260 digital amera. The hardware onfiguration of the low-ost navigation system is shown in Figure 1. Figure 1. Hardware onfiguration of low-ost navigation system. The NovAtel OEStar is a low-ost, single frequeny (L1) reeiver. It was hosen eause it outputs ode and arrier phase oservations in a simple data stream, its pass-through logging feature failitates system synhronization, and a data deoder was readily availale. A Wi-Fi LAN ard and HSDPA (high speed downlink paket aess) modem is installed to ommuniate to onnet to a NRTK NTRIP aster. Raw measurement data and antenna position will e transmitted as RTC (version 2 or 3) data. The ADIS16364 IU was seleted eause it was readily availale and El-Diasty and Pagiatakis (2009) showed that with appropriate aliration and stohasti modelling, an aurate INS/ navigation solution an e otained. Speifiations of the ADIS16364 IU are given in Tale 1. Tale 1. ADIS16374 IU speifiations (Analog Devies, 2009). 3 Gyros Initial ias error ±3 /s In-run ias staility Bias temperature oeffiient /s ±0.01 /s/ C Angular Random Walk 2 / h 3 Aelerometers Initial ias error In-run ias staility Bias temperature oeffiient Veloity Random Walk ±8 mg 0.1 mg ±0.005 mg/ C 0.12 m/s/ h ASPRS 2010 Annual Conferene

4 The KVH Azimuth 1000 digital ompass was hosen eause it met the auray requirements (±0.5 ) and eause of its small size, light weight, and low power onsumption. The Kodak Digital Siene DC260 amera was hosen eause of its low-ost and it has the aility to fix its fous at a speified setting, thus fixing the interior orientation of the amera etween exposures. The amera is ale to use an external flash to enale the time of exposure to e aptured and reorded. It has a reasonale image size (1536 x 1024 pixels), large memory, and a self-ontained power supply. ETHODOLOGY 3D Feature Extration The ojetive of the US is to aurately extrat 3D point oordinates in the mapping frame. The most ommon method to otained 3D point oordinates from image point measurements uses a least squares undle adjustment. This entails the exterior orientation (position and orientation at exposure time) and interior orientation (interior geometry and lens distortion) to e known for at least a pair of ameras. Thus the final auray of the 3D oordinates depends on the auray of the position, INS position and attitude, amera position and attitude, system synhronization, system aliration, and sensor quality. These fators will e disussed in the following setions. Time Synhronization The georeferening proess requires different data streams to e time-synhronized. The auray of georeferening is dependent on the auray with whih this an e ahieved. The synhronization auray needed is dependent on the required system performane and on the speed with whih the survey vehile moves. It is therefore, muh more ritial for airorne appliations than for marine and land vehile appliations. There are three main synhronization methods, depending on synhronization frequeny. For low frequeny appliations, the PPS signal of the reeiver triggers the anillary sensor y diret onnetion. The Novatel reeiver s pass through logging feature performs synhronization in this manner, this will e used to synhronize the digital ompass date stream. edium frequeny appliations (tens of Hertz) may use an event marker, also provided on some reeivers, to time-tag mark events from the anillary sensor. This feature an e used to time-tag the exposure times of the images aptured y the digital amera (Ellum, 2001). Synhronization for high frequeny (hundreds of hertz) systems may e performed using a entralized synhronization oard. El-Sheimy (1996) explained how to redue ommon synhronization errors in this method, suh as hardware, transmission and timing-tagging delays when synhronizing an INS. System Caliration As mentioned aove, system aliration is a prerequisite to extrating 3D information form imagery. The exterior orientation parameters are determined y a omination of and INS, the interior orientation parameters y field or laoratory aliration. The physial relationship etween a amera, an inertial measurement unit (IU), and a antenna in a S is given y El-Sheimy (1996) and shown in Figure 2. The model transforms the position of the point of interest measured in the amera (image) oordinate system, r, to the position vetor in the mapping frame, i r i, y using: r i = r( t) R ( t) R ( r s r ) (1) i i where, at time t, r is the position of the antenna, R is the rotation matrix etween the mapping and IU oordinate frames, determined using integrated IU measurements, R is the rotation matrix etween the amera and IU frames, determined from oresight aliration, r is the vetor of position differenes etween the antenna and amera, determined from lever arm aliration, and si is the sale etween the image and the mapping frames, determined using stereo tehniques, laser sanners or DT. Ellum and El-Sheimy (2002) examine three elements of integrated system aliration are examined: lever-arm aliration, oresight aliration and amera aliration. ASPRS 2010 Annual Conferene

5 Figure 2. Georeferening model. Lever Arm Caliration. The lever arm etween the antenna and perspetive enter of the amera, r ommonly determined y measuring it using onventional survey methods. The auray of this method is limited to the entimeter level eause the phase and perspetive enters of the antenna and amera, respetively, annot e diretly oserved. An alternative method is to use the differene in antenna positions determined y the oservations, r, and the amera positions determined from a undle adjustment, r requires a target field. The offset in the amera oordinate frame an e alulated using: r ( r r ), is. This tehnique = R (2) where R m is the rotation matrix etween the mapping and amera oordinate frames, whih is determined from the undle adjustment. To improve the aliration auray, multiple images are used and the orientation angles is averaged or used in a least-squares adjustment. Boresight aliration. Boresight aliration refers to the determination of the rotation matrix relating the axes of the IU to the axes of the amera, R. Unlike the lever-arm aliration, it is not possile to diretly measure the relative orientation parameters. The ommon method to perform this aliration requires R and R to e determined. This is done y olleting images of a known target field with the amera while olleting IU measurements. Photogrammetri resetion is used to estimate the amera orientation ( ω, φ, κ ) and determine the rotation matrix R. R is determined using the roll, pith and yaw measurements from the IU. R is then alulated using: ( R ) T R = R (3) To improve aliration auray, multiple images are used and the orientation angles is averaged or used in a least-squares adjustment. IU Caliration and Initial Alignment. Low-ost INS an experiene rapid degradation in the navigation solution due to the low quality of the IU. The error soures in gyros and aelerometers, mainly iases and sale errors related to non-orthogonalities of the axes, ause unstale errors in positions, veloities, and attitudes though the integration proess. Caliration methods have een developed to remove systemati error, ias and sale errors. ASPRS 2010 Annual Conferene

6 The method used to alirate a low-ost IU onsiders that the Earth s spin annot e oserved as it is ompletely uried in high level white noise. Also, the ias and sale errors are temperature-dependent and they hange from swith-on to swith-on and during the mission, thus field alirations will e applied. The multi-position aliration method desried y Shin and El-Sheimy (2001) does not require preise alignment of the IU axes and an e applied in the field. The main disadvantage of this method is the sale and non-orthogonality errors for low-ost sensors annot e estimated eause Earth rotational rate needs to e measured. Instead of using Earth rotational rate as an exitation signal, Syed et al. (2007) modified the multiposition aliration method using a rotational rate exitation from a single-axis turntale with 26 independent sensor positions (as opposed to the 18 positions in the Earth rotation method). This is the most suitale method to alirate the low-ost IU. The inertial measurements are also ontaminated with random errors, whih mainly onsist of a high frequeny and a low frequeny noise omponent. The high frequeny omponent has white noise harateristis and an e redued y using a low-pass filter. The low frequeny omponent is haraterized y orrelated noise and an e modelled using random proesses suh as, random onstant, random walk, Gauss-arkov, periodi random or autoregressive proesses (Nassar, 2003). The most ommonly used proess is the first-order Gauss-arkov proess. The INS integration assumes the initial values of veloity, position and attitude. Therefore, an initial alignment is required efore navigation. The inertial system an e initialized y first sensing the gravitational aeleration in a stationary and surveyed position. With this sensed gravity vetor, the pith and roll of the vehile platform an e oarsely resolved; however, there is an amiguity in determining the heading of the platform. The onsumer grade inertial sensor s quality is not suffiient to gyroompass y sensing the Earth s rotation to detet the east diretion. Therefore, the inertial measurement yaw axis is aligned with the north diretion from the magnetometer. This initial ondition is suffiient for a fine alignment Kalman filter proedure. Camera Caliration. Camera aliration must e performed efore using any metri or digital amera in photogrammetri appliations. The most ommon tehnique of amera aliration in lose-range photogrammetry is self-aliration eause it an e done quikly and it does not require speialised equipment nor speialised operators. This tehnique solves for the interior orientation parameters in a least-squares undle adjustment. That is, the ollinearity equations are augmented with additional parameters to aount for adjustment of the alirated prinipal point oordinates (x p, y p ), lens foal length (f), two or three elements for symmetri lens distortion (k 1, k 2, k 3 ), two elements for tangential lens distortion (p 1, p 2 ). In addition, the position (X o, Y o, Z o ) and the orientation ( ω, φ, κ ) parameters of the amera are solved for. El-Sheimy (1996) provided details aout the approah. Inertial Navigation System The inertial navigation system is omprised of an IU, the platform on whih it is mounted and the omputer that performs the alulations needed to transform sensed aelerations and angular rates into navigationally useful information: position, veloity, and attitude. The dynami equations show the ehaviour of the states in terms of the linear (linearized) differential navigation equations (pertured navigation equation). The nonlinear navigation dynami system diagram is shown in Figure 3. Figure 3. Inertial navigation proessing. ASPRS 2010 Annual Conferene

7 In strapdown systems, the quaternion method to represent attitude is preferred over oth Euler angle and the diretion osine methods eause it offers aurate and effiient omputation methods without singularities. Kong (2000) desries a quaternion approah of the INS algorithm for low-ost IU. Kalman Filter Design A filtering tehnique is applied to optimally estimate the navigation solution (position, veloity and attitude) together with the sensor errors y omining the measurements from the, IU and digital ompass in a Kalman filter. Hasan et. al. (2009) presented a omparative study of various Kalman filter onfigurations applied to air, land and marine navigation appliations. Skaloud (1999) presented and analysed different Kalman Filter implementations used to estimate the state vetor. The indiret (error state) implementation is very popular in terrestrial aided INS eause the dynamis are low frequeny error propagation equations. These equations are adequately represented as linear, as opposed to the highly non-linear model in the total state desription. The losed-loop (feedak) implementation is hosen for this appliation eause it generally performs etter than the open-loop (feedforward) filter. The loosely-oupled (deentralized) filtering approah was hosen over the tightlyoupled (entralized) filter eause of its modularity and smaller filter size. With a loosely oupled integration, a navigation proessor alulates position and veloity using oservales only. An external navigation filter omputes position, veloity and attitude from the raw inertial sensor measurements and uses the position and veloity to alirate INS position errorsδ R veloity errors, while the filtered ompass attitude is used to alirate the INS angular errorsψ. The model is augmented y some dominant sensor errors, suh as aelerometer iases δα and gyro driftsδω. In the feedak onfiguration, the estimates of the sensor errors are used to orret the raw inertial sensor measurements efore they are integrated in the INS. Figure 4 illustrates the feedak onfiguration of the /INS filter. Figure 4. Kalman filter design. CONCLUDING REARKS This projet aims to develop an unmanned moile mapping system (US) using low-ost sensors onoard a low-ost unmanned ground vehile (UGV). The US will provide near-ontinuous positioning of the platform and simultaneously ollet 3D geo-spatial data. Diret georeferening will e used, with no external information, suh as ground ontrol, exept for the ase station. Navigation will e ased on single frequeny differential, loosely oupled with a low-ost digital ompass and INS (Inertial Navigation System) ased on ES (iro Eletroni ehanial Systems) tehnology. The navigation system will autonomously provide position, veloity, and attitude data in a mapping referene frame together with measurements of linear aeleration and angular rate in the ody axes. As storage apaity is limited due to payload restritions, diret downlink of data through wireless ommuniations is used in onjuntion with onoard proessing. ASPRS 2010 Annual Conferene

8 ACKNOWLEDGEENTS This researh is finanially supported y the Natural Sienes and Engineering Researh Counil of Canada (NSERC). The ontriutions of Prof. Dr Regina Lee, Spae Engineering, York University, and Chris Fernando, Researh Assistant, in the hardware design of the platform are muh appreiated. REFERENCES Analog Devies In. Six Degrees of Freedom Inertial Sensor: ADIS Analog Devies In: Norwood, A, USA, Caruso,., Appliations of agneti Sensors for Low Cost Compass Systems. In Proeedings of IEEE Positioning, Loation, and Navigation Symposium (PLANS) San Diego. arh pp El-Diasty. and S. Pagiatakis, A Rigorous Temperature-Dependent Stohasti odelling and Testing for ES-Based Inertial Sensor Errors. Sensors. 2009; 9(11): Ellum, C., The Development of a Bakpak oile apping System..E thesis. University of Calgary, Department of Geomatis Engineering, Alerta Canada. Ellum, C. and N. El-Sheimy, The Development of a Bakpak oile apping System. Int. Ar. Photogrammetry and Remote Sense, vol. XXXII, Part 2W1. Ellum, C. and N. El-Sheimy, The aliration of image-ased moile mapping systems. Proeedings of the 2nd Symposium on Geodesy for Geotehnial and Strutural Engineering. ay 21-24, Berlin, Germany. The International Assoiation of Geodesy (IAG). El-Sheimy, N., The Development of VISAT - A oile Survey System For GIS Appliations. Ph.D. Dissertation, University of Calgary, Department of Geomatis Engineering, Alerta Canada. Hasan, A., K. Samsudin, A. Ramli, R. Azmir, and S. Ismaeel, A Review of Navigation Systems (Integration and Algorithms), Australian Journal of Basi and Applied Sienes, 3(2): Kong, X., Inertial navigation system algorithm for low ost IU, Ph.D. Thesis, The University of Sydney. Li, B., A ost effetive synhronization system for multisensor integration, ION GNSS 2004, Long Beah, USA, Septemer, Li, R., oile apping: An Emerging Tehnology for Spatial Data Aquisition. Photogrammetri Engineering and Remote Sensing. 63(9). pp Li, X., Photogrammetri Investigation into Low-Resolution Digital Camera Systems. Ph.D. dissertation. Department of Geodesy and Geomatis Engineering Tehnial Report No University of New Brunswik. Frederition, New Brunswik, Canada. 180 pp. Nassar, S., Improving the Inertial navigation System (INS) Error odel for INS and INS/D Appliations. Ph.D. Thesis, Department of Geomatis Engineering, University of Calgary, Calgary, Alerta, Canada, UCGE Report No Shin, E.-H. and N. El-Sheimy, N Auray Improvement of Low Cost INS/ for Land Appliations, ION NT, San Diego, CA, pp Skaloud, J., Optimizing Georeferening of Airorne Survey Systems y INS/D. Ph.D. Thesis, Dept. of Geomatis Eng., The University of Calgary, Calgary, Alerta, Canada. Syed, Z. F., P. Aggarwal, C. Goodall, X. Niu, and N. El-Sheimy, A new multi-position aliration method for ES inertial navigation systems. easurements Siene and Tehnology, No. 18 (2007), pp Takasu, T., and A. Yasuda, Development of the low-ost RTK- reeiver with an open soure program pakage RTKLIB, International Symposium on /GNSS, International Convention Center Jeju, Korea. ASPRS 2010 Annual Conferene