Evaluation of an UWB localization system in static and dynamic

Abstract

Applications in the context of the industry 4.0 need a precise localization. Indoor localization remains an open problem. Among the possible solutions, we see the emergence of Ultra Wide Band(UWB)-methods. The aim of this article is to evaluate an UWB system in order to estimate the position of a person in indoor environments. We have evaluated an UWB system to obtain results of the 3D localization of a moving person in buildings environment in real time. For that purpose, static and dynamic tests were established using a ground truth based on a motion capture system with a millimetric accuracy.

Keywords

• Indoor localization
• Ultra WideBand (UWB)

Introduction

RSSI is available in many telecommunication standards. More recently multilateration (measurement from transmission time di erences called Time Di erence of Arrival or TDoA between at least two transmitters and one receiver; transmitters being perfectly synchronized). The fact that the system to be located is itself active increases considerably the localization accuracy. There is a wide range of systems in this eld. A review of these solutions shows that an accurate localization around 30cm is possible [ 14 ]. However, this performance degrades severely when there is no direct Line-Of-Sight between the terminals ( xed anchor in the building) and the receiver (Tag placed on the moving person) to be located. The accuracy of these solutions depends on the environment in which the system will be deployed, which is related to the use case. It should be noted that there is a strong excitement caused by the release of UWB radio solutions to the market wich promise to be even more e cient than the current ones.

The contribution of this work is a dynamic test with a millimeter accuracy ground truth in real time, to evaluate its precision and its accuracy, and to de ne if UWB localization sensors can be used for gesture recognition in 3D space.

This paper is divided into two parts. First, we study the performance a UWB-based localization sensor named "UWB" in the rest of this paper, and evaluate the speci cation in a free space surrounded by metallic objects such as robots, infrastructure or doors in our laboratory. Secondly, we propose a complete evaluation of the system behaviour in static and dynamic conditions to see if UWB can be used to obtain an accurate 3D trajectory for gesture recognition. 2

State of the art of indoor localization technologies

For human-machine Interaction in the context of industry 4.0, it is necessary to be able to locate the operator in a large environment (above 20m range) and with good accuracy (with a 0.1 meter accuracy). Localization in an indoor environment will be used in industry 4.0, based on Maultz thesis [ 14 ] there are 13 technologies shown in Table 1 that can answer indoor-localization.

Systems based on cameras for indoor localization approaches are used in di erent ways. The rst one is to have a 3D building model as a reference. The second system is the socalled viewbased approach. It consists in taking the current view of a mobile camera and comparing it with previously captured view sequences. This system arrived at centimeter accuracy and can cover a building [ 17 ]. The third system is coded targets used for point identi cation to locate a person. The system can know where the person is with a centimeter accuracy but does not store the trajectory made by the person [ 12 ]. The fourth system is the projection of reference points in the environment. This system needs a direct view of the same surface and it can be used for tracking with a millimeter accuracy [ 23 ]. The fth system is using one camera or many cameras without reference by observing position change. This system can reach sub-centimeter accuracy and can cover 30m2.

Infrared systems based on active beacons or using natural radiation are mainly used for rough positional estimation or for detecting the presence of a person in a room. They have centimetermeter accuracy level and can cover 1-5 meters in static conditions. They are a common alternative to optical systems operating in the visible light spectrum. An accuracy of 4cm has been reported and people can be tracked up to a distance of 5m [ 11 ] and centimeter accuracy in a retail store [ 3 ].

Tactile and polar systems have m-mm accuracy and can cover an entire room. The polar point method uses a distance measurement and an angular measurement from the same beacon to determine the coordinates of a nearby station. Tactile systems are high precision mechanical instruments which measure positions by touching an object with a calibrated pointer. We can not track an entire trajectory in 3D [ 14 ].

Localization systems based on propagation of sound waves have a centimeter accuracy and can cover 2-10 square meters. The sound is a mechanical wave so positioning systems use air and building materials as means of propagation [ 25 ]. Mechanical waves are not su ciently accurate in indoor environments for industrial applications due to multipath which is a phenomenon that occurs when a radio signal propagates through several paths and is received on an antenna.

WLAN/WIFI systems have one meter of accuracy and can cover 20 50m2. Distance estimation using WLAN is generally possible from RSSI (Received Signal Strength Indication), ToA (Time of Arrival), TDoA (Time Di erence of Arrival) and RTT (Round-Trip Time). The accuracy of this kind of systems is not enough to handle an accurate trajectory estimation in the 3D space [ 9 ] [ 5 ].

RFID has dm-m level of accuracy and can cover 1-50 m. Most RFID systems rely on proximity detection of permanently mounted tags to locate a person. The accuracy of an RFID system is directly related to the density of tags deployment and reading ranges so it can be expensive in large areas. RFID systems can not do 3D trajectory tracking because most of them rely on proximity detection of permanently mounted tags to locate mobile readers [ 20 ].

Pseudolites use a similar methods of localization as the Global Navigation System (GNSS) but in indoor environments. Several di culties such as multipath mitigation, time synchronization and ambiguity solving have limited this system to few applications in GNSS-challenged environments such as open pit mines [ 10 ] [ 8 ]. It can cover 10 1000m2 area and have a cm-dm accuracy.

Other radio-frequency systems such as Zigbee, bluetooth, Digital Television, Cellular networks, Radar, FM radio, Phones based on Digital Enhanced Cordless Technology have for best submillimeters accuracy and can cover 10-1000 square meters. However, performance levels and applicability vary greatly depending on several factors such as the use of preexisting reference infrastructure, pervasiveness of devices, signal ranges, power levels [ 14 ]. The best systems have an accuracy of 1m and can cover a building.

Inertial navigation systems is usually fused with complementary sensors which provide absolute location information due to drift and have few meters accuracy [ 14 ]. Footmounted systems can make use of zero velocity during the foot is in stance stage and have therefore a lower drift and can improve the accuracy below 1m [ 18 ] of the travelled distance. Compared to IMUs mounted at other body parts [ 21 ] with drifts being typically larger.

System based on magnetic eld has centimeter-accuracy and can cover 10 meters area [ 4 ]. Different approaches range from systems dedicated for medical purposes using an arti cial quasi static magnetic eld with less than 1 m3 volume operating at mm-accuracy level. In indoor environments, with the same approach, we can have few meters accuracy covering storage aisles and a building [ 24 ] [ 1 ] but we can be perturbed by the magnetic eld induced by electric motors inside industrial buildings.

Infrastructure systems are technologies that use the existing building infrastructure or embed additional infrastructure into the building materials such as Power Lines positioning, Floor Tiles, Fluorescent Lamps or leaky feeder cables as described in [ 14 ]. These systems have cm-m level of accuracy.

Technology Typical Accuracy Typical Coverage

Cameras 0.1mm-dm 1-10 Infrared cm-m 1-5m Tactile & Polar Systems um-mm 3-2000m Sound cm 2-10m WLAN/WIFI m 20-50m RFID dm-m 1-50m Ultra WideBand cm-m 1-50m High Sensitive GNSS 10m 'global' Pseudolites cm-dm 10-1000m Other Radio Frequencies m 10-1000m Inertial Navigation 1% 10-100m Magnetic Systems mm-cm 1-20m

Infrastructure Systems cm-m building

UWB (Ultra WideBand) is less expensive than others technologies and can be accurate even in Non-Line-Of-Sight (NLOS) conditions. It has the ability to carry signals through doors and other obstacles that tend to re ect signals with more limited bandwidth and higher power levels [ 7 ]. Syberfeldt et al. [ 22 ] proposed a review of existing techniques and systems for locating operators in a smart factory. In this comparison, we can see that UWB has a high precision compared to others indoor localization system and a medium cost for the industry. Alari et al. [ 2 ] established a Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis of UWB systems. The main bene ts of UWB systems are a low-power consumption and the ability to penetrate di erent kinds of materials. This is due to the very short pulses that do not interfere with most of the existing radio systems. The weakness of UWB is the synchronization: due to his short pulses, it may take time to synchronize. This article comforts our choice of UWB as the best system for indoor localization. 3 3.1

Experimental Setup and Evaluation

Experimental setup

We decided to evaluate a UWB system from Decawave since it seems to be the most accurate [ 19 ]. To evaluate this system, four anchors must rst be placed in the room used for indoor localization. We align anchors with laser measurements. One Anchor is chosen as reference (initialization at x=0 and y=0), and we must obtain the position of each anchor according to the initialization anchor as shown in Figure 1a.

(a) Four static anchors in purple are placed in a rectangle. The tag is placed (b) Placement of anchors in the laborain the area of the anchors in LOS. tory.

Fig. 1: Our UWB setup

We obtain the position of each anchors with a VICON motion capture system. The area of testing in Figure 1a is in the lab with a LOS condition and in an industrial environment with a metallic structure, robots and a metallic door close to the testing area as shown in Figure 1b. The Tag is mounted on a support and placed on a wooden cart with a height of 0.7m to verify the trajectory in 3D in the inner area of the UWB system. 3.2

Tests and Evaluation

Static Measurement Precision The rst test is to place the tag in the inner area of the UWB anchors. This test will give us the distribution of the UWB points when the tag is static. The results of the static test are given in Table 2. The mean error on the 3 XYZ axes is 1cm and the average range is 10cm. The values are distributed around the average value with a standard deviation of 0:011m. This means that the UWB system is not precise in a static situation, but has a high accuracy of 10cm on average. UWB is accurate up to 10cm in static and behaves like a sphere around the target with a range value of 10cm. When a person is not moving, we know where the person is with an accuracy of 10cm.

Static

LOS test X-axis Y-axis Z-axis 2D

3D eMrreoarn 0.01m 0.01m 0.01m 0.01m 0.01 m Range 0.09m 0.10m 0.11m 0.095m 0.1m dSteavniadtaiordn 0.010m 0.014m 0.011m 0.012m 0.011m

Dynamic Measurement Evaluation and Precision of a trajectory With the Vicon system [ 15 ], we will compare the exact 3D point of the Vicon with the 3D point of UWB in real-time. The rst test we made was a trajectory inside the inner area of the UWB anchors. The test was made in the laboratory in LOS with industrial conditions.

In XY measurement we have 21cm of accuracy as shown in Table 3. That means we have 78% of precision for this trajectory in XY. We can use UWB for real time localization and in dynamic. We have 0:24cm of accuracy in 3D (XYZ) only 40% of values for Z-axis are precise, they are not around the mean value. The Z-axis is not trustable for dynamic localization and for motion gesture recognition. This result shows that, in dynamic localization, we can use UWB for motion tracking with X-Y axis in real time but not in 3D because the Z-axis is not trustable. Figure 2 highlights that the Z-axis measurements are wavy.

Dynamic Measurement Evaluation and Precision of mapping The third test is to realize a mapping of the inner area and outer area of the UWB system to evaluate its behaviour. We covered the maximum area and try to see if the accuracy/precision changed. Comparing to our rst test we have an accuracy of 23cm in the inner area and 25cm in the outer area in 2D and 23cm and 24cm in 3D that is close to our rst result in dynamic localization shown in Table 3. These two tests

Dmyeansaumreic X-axis Y-axis Z-axis 2D 3D Mean error 0.20m 0.22m 0.32m 0.21m 0.24m Range 0.73m 0.64m 0.87m 0.65m 0.75m Sdteavniadtaiordn 0.13m 0.14m 0.29m 0.135m 0.186m show that UWB is homogeneous for a covered area even outside of the area de ned by its anchors in industrial LOS conditions. UWB is really good for dynamic localization in indoor environments. We lose precision compared to our static results. We had 10cm accuracy in static measurement, we had 0:24m accuracy in dynamic localization as shown in Table 4.

UWB mapping X-axis Y-axis Z-axis 2D 3D

rMean error 0.30 m 0.17m 0.23m 0.23m 0.23m enRange 1.07m 0.60m 1.37m 0.56m 1.01m InSdteavniadtaiordn 0.18m 0.001m 0.20m 0.18m 0.12m rMean error 0.23m 0.27m 0.23m 0.25m 0.24m teuRange 0.98m 1.05m 1.03m 1.01m 1.02m OSdteavniadtaiordn 0.028m 0.15m 0.19m 0.09m 0.12m

Study of the in uence of anchors This test was made to verify the behavior of UWB in the inner area of UWB in dynamics with four and six anchors. We place four anchors exactly as in the Figure 1a and one more on the oor in one corner of our cube. And then two more on the oor in corners. With the use of 4 anchors, the 3D positioning error is 0:24 0:19cm with a Z error of 0:32 0:29cm. The number of anchors mainly in uences the Z measurement: with 6 anchors, the Z error is 0:16 0:01cm while the 3D error decreases slightly: 0:20 0:12cm.

Conclusion

In this article, we describe the behaviour of an Ultra WideBand system in static and dynamic cases by comparison with a ground truth obtained with a motion capture system. We have an evaluation of the precision and accuracy of the UWB system which is really good in the X-Y axes but not trustable along the Z-axis. We con rm that precision and accuracy are better by adding anchors when performing dynamic localization. UWB systems can not be used for gesture recognition. Nevertheless, they can be a really good choice for localization, even in dynamic, and can be more robust if we add more anchors. Z-axis needs to be improved, mostly in terms of precision, and this can be achieved by data fusion with other sensors. Our future works will be the improvement of the accuracy and precision of the system by the addition of an IMU and a barometer.

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