Abstract

For mobile robots, localization is essential for navigation and spatial correlation of its collected data. However, localization in Global Positioning System-denied environments such as underwater has been challenging. Light-emitting diode (LED)-based optical localization has been proposed in the literature, where the bearing angles extracted from the line-of-sight of the robot viewed from a pair of base nodes (also known as beacon nodes) are used to triangulate the position of the robot. The state-of-the-art in this approach uses a stop-and-go motion for the robot in order to ensure an accurate position measurement, which severely limits the mobility of the robot. This work presents an LED-based optical localization scheme for a mobile robot undergoing continuous motion, despite the two angles in each measurement cycle being captured at different locations of the robot. In particular, the bearing angle measurements are captured by the robot one at a time and are properly correlated with respect to the base nodes by utilizing the velocity prediction from Kalman filtering. The proposed system is evaluated in simulation and experiments, with its performance compared to the traditional state-of-the-art approach where the two angle measurements in each cycle are used directly to compute the position of the robot. In particular, the experimental results show that the average position and velocity estimation errors are reduced by 55% and 38%, respectively, when comparing the proposed method to the state-of-the-art.

References

1.
Kim
,
M.
, and
Chong
,
N. Y.
,
2007
, “
RFID-Based Mobile Robot Guidance to a Stationary Target
,”
Mechatronics
,
17
(
4–5
), pp.
217
229
. 10.1016/j.mechatronics.2007.01.005
2.
Wanasinghe
,
T. R.
,
Mann
,
G. K. I.
, and
Gosine
,
R. G.
,
2014
, “
Decentralized Cooperative Localization for Heterogeneous Multi-Robot System Using Split Covariance Intersection Filter
,” Canadian Conference on Computer and Robot Vision (
CRV
), Montreal, QC, Canada, May 6–9, pp.
167
174
.10.1109/CRV.2014.30
3.
Wang
,
K.
,
Liu
,
Y.
, and
Li
,
L.
,
2014
, “
A Simple and Parallel Algorithm for Real-Time Robot Localization by Fusing Monocular Vision and Odometry/AHRS Sensors
,”
IEEE/ASME Trans. Mechatronics
,
19
(
4
), pp.
1447
1457
.10.1109/TMECH.2014.2298247
4.
Kim
,
A.
, and
Eustice
,
R.
,
2009
, “
Pose-Graph Visual Slam With Geometric Model Selection for Autonomous Underwater Ship Hull Inspection
,”
IEEE/RSJ International Conference on Intelligent Robots and Systems
, St. Louis, MO, Oct. 10–15, pp.
1559
1565
.10.1109/IROS.2009.5354132
5.
Zachár
,
G.
,
Vakulya
,
G.
, and
Simon
,
G.
,
2017
, “
Design of a VLC-Based Beaconing Infrastructure for Indoor Localization Applications
,” IEEE International Instrumentation and Measurement Technology Conference (
I2MTC
), Turin, Italy, May 22–25, pp.
1
6
.10.1109/I2MTC.2017.7969837
6.
Bergen
,
M. H.
,
Jin
,
X.
,
Guerrero
,
D.
,
Chaves
,
H. A. L. F.
,
Fredeen
,
N. V.
, and
Holzman
,
J. F.
,
2017
, “
Design and Implementation of an Optical Receiver for Angle-of-Arrival-Based Positioning
,”
J. Lightwave Technol.
,
35
(
18
), pp.
3877
3885
. 10.1109/JLT.2017.2723978
7.
Bergen
,
M. H.
,
Schaal
,
F. S.
,
Klukas
,
R.
,
Cheng
,
J.
, and
Holzman
,
J. F.
,
2018
, “
Toward the Implementation of a Universal Angle-Based Optical Indoor Positioning System
,”
Front. Optoelectron.
,
11
(
2
), pp.
116
127
. 10.1007/s12200-018-0806-0
8.
Browne
,
A. F.
, and
Padgett
,
S. T.
,
2018
, “
Novel Method of Determining Vehicle Cartesian Location Using Dual Active Optical Beacons and a Rotating Photosensor
,”
IEEE Sens. Lett.
,
2
(
4
), pp.
1
4
. 10.1109/LSENS.2018.2873841
9.
Peula
,
J. M.
,
Urdiales
,
C.
, and
Sandoval
,
F.
,
2010
, “
Explicit Coordinated Localization Using Common Visual Objects
,”
IEEE International Conference on Robotics and Automation
, Anchorage, AK, May 3–7, pp.
4889
4894
.10.1109/ROBOT.2010.5509398
10.
Easton
,
A.
, and
Cameron
,
S.
,
2006
, “
A Gaussian Error Model for Triangulation-Based Pose Estimation Using Noisy Landmarks
,”
IEEE Conference on Robotics, Automation and Mechatronics
, Bangkok, Thailand, June 1–3, pp.
1
6
.10.1109/RAMECH.2006.252663
11.
Font-Llagunes
,
J. M.
, and
Batlle
,
J. A.
,
2009
, “
Consistent Triangulation for Mobile Robot Localization Using Discontinuous Angular Measurements
,”
Rob. Auton. Syst.
,
57
(
9
), pp.
931
942
.10.1016/j.robot.2009.06.001
12.
Font
,
J. M.
, and
Batlle
,
J. A.
,
2006
, “
Mobile Robot Localization. Revisiting the Triangulation Methods
,”
IFAC Proc. Vols.
,
39
(
15
), pp.
340
345
.10.3182/20060906-3-IT-2910.00058
13.
Olsen
,
C. F.
,
2000
, “
Probabilistic Self-Localization for Mobile Robots
,”
IEEE Trans. Rob. Autom.
,
16
(
1
), pp.
55
66
.10.1109/70.833191
14.
Giuffrida
,
F.
,
Morasso
,
P.
,
Vercelli
,
G.
, and
Zaccaria
,
R.
,
1996
, “
Active Localization Techniques for Mobile Robots in the Real World
,”
Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems
, Vol.
3
, Osaka, Japan, Nov. 8, pp.
1312
1318
.10.1109/IROS.1996.568986
15.
Rahul Sharma
,
K.
,
Honc
,
D.
, and
Dusek
,
F.
,
2014
, “
Sensor Fusion for Prediction of Orientation and Position From Obstacle Using Multiple IR Sensors an Approach Based on Kalman Filter
,”
International Conference on Applied Electronics
, Pilsen, Czech Republic, Sept. 9–10, pp.
263
266
.10.1109/AE.2014.7011716
16.
Prabha
,
C.
,
Supriya
,
M. H.
, and
Pillai
,
P. R. S.
,
2009
, “
Improving the Localization Estimates Using Kalman Filters
,” International Symposium on Ocean Electronics (
SYMPOL 2009
)), Cochin, India, Nov. 18–20, pp.
190
195
.10.1109/SYMPOL.2009.5664196
17.
Xu
,
S.
,
Ou
,
Y.
, and
Wu
,
X.
,
2019
, “
Learning-Based Adaptive Estimation for AOA Target Tracking With Non-Gaussian White Noise
,” IEEE International Conference on Robotics and Biomimetics (
ROBIO
), Dali, China, Dec. 6–8, pp.
2233
2238
.10.1109/ROBIO49542.2019.8961815
18.
Rana
,
M. M.
,
Halim
,
N.
,
Rahamna
,
M. M.
, and
Abdelhadi
,
A.
,
2020
, “
Position and Velocity Estimations of 2D-Moving Object Using Kalman Filter: Literature Review
,” 22nd International Conference on Advanced Communication Technology (
ICACT
), Phoenix Park, South Korea, Feb. 16–19, pp.
541
544
.10.23919/ICACT48636.2020.9061241
19.
Feng
,
H.
,
Liu
,
C.
,
Shu
,
Y.
, and
Yang
,
O. W.
,
2015
, “
Location Prediction of Vehicles in VANETs Using a Kalman Filter
,”
Wireless Pers. Commun.
,
80
(
2
), pp.
543
559
.10.1007/s11277-014-2025-3
20.
Rui
,
G.
, and
Chitre
,
M.
,
2016
, “
Cooperative Multi-AUV Localization Using Distributed Extended Information Filter
,” IEEE/OES Autonomous Underwater Vehicles (
AUV
), Tokyo, Japan, Nov. 6–9, pp.
206
212
.10.1109/AUV.2016.7778673
21.
Emokpae
,
L. E.
,
DiBenedetto
,
S.
,
Potteiger
,
B.
, and
Younis
,
M.
,
2014
, “
UREAL: Underwater Reflection-Enabled Acoustic-Based Localization
,”
IEEE Sens. J.
,
14
(
11
), pp.
3915
3925
. November10.1109/JSEN.2014.2357331
22.
Akyildiz
,
I. F.
,
Wang
,
P.
, and
Sun
,
Z.
,
2015
, “
Realizing Underwater Communication Through Magnetic Induction
,”
IEEE Commun. Mag.
,
53
(
11
), pp.
42
48
.10.1109/MCOM.2015.7321970
23.
Tan
,
X.
,
2011
, “
Autonomous Robotic Fish as Mobile Sensor Platforms: Challenges and Potential Solutions
,”
Mar. Technol. Soc. J.
,
45
(
4
), pp.
31
40
. 10.4031/MTSJ.45.4.2
24.
Tian
,
B.
,
Zhang
,
F.
, and
Tan
,
X.
,
2013
, “
Design and Development of an LED-Based Optical Communication System for Autonomous Underwater Robots
,” IEEE/ASME International Conference on Advanced Intelligent Mechatronics (
AIM
), Wollongong, NSW, Australia, July 9–12, pp.
1558
1563
.10.1109/AIM.2013.6584317
25.
Solanki
,
P. B.
,
Al-Rubaiai
,
M.
, and
Tan
,
X.
,
2016
, “
Extended Kalman Filter-Aided Alignment Control for Maintaining Line of Sight in Optical Communication
,”
American Control Conference
, Boston, MA, July 6–8, pp.
4520
4525
.10.1109/ACC.2016.7526064
26.
Brundage
,
H.
,
2010
, “
Designing a Wireless Underwater Optical Communication System
,” Master's thesis,
Massachusetts Institute of Technology
, Boston, MA.
27.
Doniec
,
M.
,
2013
, “
Autonomous Underwater Data Muling Using Wireless Optical Communication and Agile AUV Control
,” Ph.D. thesis,
Massachusetts Institute of Technology
, Cambridge, MA.
28.
Anguita
,
D.
,
Brizzolara
,
D.
, and
Parodi
,
G.
,
2009
, “
Building an Underwater Wireless Sensor Network Based on Optical: Communication: Research Challenges and Current Results
,”
Third International Conference on Sensor Technologies and Applications
, Athens, Greece, June 18–23, pp.
476
479
.10.1109/SENSORCOMM.2009.79
29.
Anguita
,
D.
,
Brizzolara
,
D.
, and
Parodi
,
G.
,
2010
, “
Optical Wireless Communication for Underwater Wireless Sensor Networks: Hardware Modules and Circuits Design and Implementation
,”
OCEANS MTS/IEEE SEATTLE
, Seattle, WA, Sept. 20–23, pp.
1
8
.10.1109/OCEANS.2010.5664321
30.
Rust
,
I. C.
, and
Asada
,
H. H.
,
2012
, “
A Dual-Use Visible Light Approach to Integrated Communication and Localization of Underwater Robots With Application to Non-Destructive Nuclear Reactor Inspection
,”
IEEE International Conference on Robotics and Automation
(
ICRA
), Saint Paul, MN, May 14–18, pp.
2445
2450
.10.1109/ICRA.2012.6224718
31.
Simpson
,
J. A.
,
Hughes
,
B. L.
, and
Muth
,
J. F.
,
2012
, “
Smart Transmitters and Receivers for Underwater Free-Space Optical Communication
,”
IEEE J. Sel. Areas Commun.
,
30
(
5
), pp.
964
974
.10.1109/JSAC.2012.120611
32.
Al-Rubaiai
,
M.
,
2015
, “
Design and Development of an LED-Based Optical Communication System
,” Master's thesis,
Michigan State University
, East Lansing, MI.
33.
Solanki
,
P. B.
,
Al-Rubaiai
,
M.
, and
Tan
,
X.
,
2018
, “
Extended Kalman Filter-Based Active Alignment Control for LED Optical Communication
,”
IEEE/ASME Trans. Mechatronics
,
23
(
4
), pp.
1501
1511
. 10.1109/TMECH.2018.2841643
34.
Qiu
,
K.
,
Zhang
,
F.
, and
Liu
,
M.
,
2016
, “
Let the Light Guide Us: VLC-Based Localization
,”
IEEE Rob. Autom. Mag.
,
23
(
4
), pp.
174
183
. 10.1109/MRA.2016.2591833
35.
Liang
,
Q.
,
Lin
,
J.
, and
Liu
,
M.
,
2019
, “
Towards Robust Visible Light Positioning Under LED Shortage by Visual-Inertial Fusion
,” International Conference on Indoor Positioning and Indoor Navigation (
IPIN
), Pisa, Italy, Sept. 30–Oct. 3, pp.
1
8
.10.1109/IPIN.2019.8911760
36.
Armstrong
,
J.
,
Sekercioglu
,
Y. A.
, and
Neild
,
A.
,
2013
, “
Visible Light Positioning: A Roadmap for International Standardization
,”
IEEE Commun. Mag.
,
51
(
12
), pp.
68
73
. 10.1109/MCOM.2013.6685759
37.
Li
,
L.
,
Hu
,
P.
,
Peng
,
C.
,
Shen
,
G.
, and
Zhao
,
F.
,
2014
, “
Epsilon: A Visible Light Based Positioning System
,”
11th USENIX Symposium on Networked Systems Design and Implementation (NSDI 14)
, Seattle, WA, pp.
331
334
.
38.
Nguyen
,
N. T.
,
Nguyen
,
N. H.
,
Nguyen
,
V. H.
,
Sripimanwat
,
K.
, and
Suebsomran
,
A.
,
2014
, “
Improvement of the VLC Localization Method Using the Extended Kalman Filter
,”
TENCON 2014–2014 IEEE Region 10 Conference
, Bangkok, Thailand, Oct. 22–25, pp.
1
6
.10.1109/TENCON.2014.7022416
39.
Liang
,
Q.
,
Sun
,
Y.
,
Wang
,
L.
, and
Liu
,
M.
,
2021
, “
A Novel Inertial-Aided Visible Light Positioning System Using Modulated LEDs and Unmodulated Lights as Landmarks
,”
IEEE Trans. Autom. Sci. Eng.
, pp.
1
19
. 10.1109/TASE.2021.3105700
40.
Keskin
,
M. F.
,
Sezer
,
A. D.
, and
Gezici
,
S.
,
2018
, “
Localization Via Visible Light Systems
,”
Proc. IEEE
,
106
(
6
), pp.
1063
1088
. 10.1109/JPROC.2018.2823500
41.
Bai
,
L.
,
Yang
,
Y.
,
Guo
,
C.
,
Feng
,
C.
, and
Xu
,
X.
,
2019
, “
Camera Assisted Received Signal Strength Ratio Algorithm for Indoor Visible Light Positioning
,”
IEEE Commun. Lett.
,
23
(
11
), pp.
2022
2025
. 10.1109/LCOMM.2019.2935713
42.
Giguere
,
P.
,
Rekleitis
,
I.
, and
Latulippe
,
M.
,
2012
, “
I See You, You See Me: Cooperative Localization Through Bearing-Only Mutually Observing Robots
,”
IEEE/RSJ International Conference on Intelligent Robots and Systems
, Vilamoura-Algarve, Portugal, Oct. 7–12, pp.
863
869
.10.1109/IROS.2012.6385965
43.
Suh
,
J.
,
You
,
S.
,
Choi
,
S.
, and
Oh
,
S.
,
2016
, “
Vision-Based Coordinated Localization for Mobile Sensor Networks
,”
IEEE Trans. Autom. Sci. Eng.
,
13
(
2
), pp.
611
620
. April10.1109/TASE.2014.2362933
44.
Concha
,
A.
,
Drews
,
P.
, Jr
,
Campos
,
M.
, and
Civera
,
J.
,
2015
, “
Real-Time Localization and Dense Mapping in Underwater Environments From a Monocular Sequence
,”
OCEANS 2015–Genova
, Genova, Italy, May 18–21, pp.
1
5
.10.1109/OCEANSGenova.2015.7271476
45.
Liu
,
J.
,
Gong
,
S.
,
Guan
,
W.
,
Li
,
B.
,
Li
,
H.
, and
Liu
,
J.
,
2020
, “
Tracking and Localization Based on Multi-Angle Vision for Underwater Target
,”
Electronics
,
9
(
11
), p.
1871
.10.3390/electronics9111871
46.
Greenberg
,
J. N.
, and
Tan
,
X.
,
2016
, “
Efficient Optical Localization for Mobile Robots Via Kalman Filtering-Based Location Prediction
,”
ASME
Paper No. DSCC2016-9917.10.1115/DSCC2016-9917
47.
Greenberg
,
J. N.
, and
Tan
,
X.
,
2017
, “
Kalman Filtering-Aided Optical Localization of Mobile Robots: System Design and Experimental Validation
,”
ASME
Paper No. DSCC2017-5368.10.1115/DSCC2017-5368
48.
Greenberg
,
J. N.
, and
Tan
,
X.
,
2020
, “
Dynamic Optical Localization of a Mobile Robot Using Kalman Filtering-Based Position Prediction
,”
IEEE/ASME Trans. Mechatronics
,
25
(
5
), pp.
2483
2492
. October10.1109/TMECH.2020.2980434
49.
Greenberg
,
J. N.
, and
Tan
,
X.
,
2021
, “
Sensitivity-Based Data Fusion for Optical Localization of a Mobile Robot
,”
Mechatronics
,
73
, p.
102488
.10.1016/j.mechatronics.2021.102488
50.
Solanki
,
P. B.
,
Bopardikar
,
S. D.
, and
Tan
,
X.
,
2020
, “
Active Alignment Control-Based LED Communication for Underwater Robots
,” IEEE/RSJ International Conference on Intelligent Robots and Systems (
IROS
), Las Vegas, NV, Oct. 24–Jan. 24, pp.
1692
1698
.10.1109/IROS45743.2020.9341442
51.
Greenberg
,
J. N.
, and
Tan
,
X.
,
2020
, “
Dynamic Prediction-Based Optical Localization of a Robot During Continuous Movement
,”
ASME
Paper No. DSCC2020-3288. 10.1115/DSCC2020-3288
52.
Kalman
,
R. E.
,
1960
, “
A New Approach to Linear Filtering and Prediction Problems
,”
ASME J. Basic Eng.
,
82
(
1
), pp.
35
45
. 10.1115/1.3662552
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