Detecting,localizing,and tracking an unknown number of moving targets using a team of mobile robots

Abstract

Target tracking is a fundamental problem in robotics research and has been the subject of detailed studies over the years. In this paper, we generate a data-driven target model from a real-world dataset of taxi motions. This model includes target motion, appearance, and disappearance from the search area. Using this target model, we introduce a new formulation of the mobile target tracking problem based on the mathematical concept of random finite sets. This formulation allows for tracking an unknown and dynamic number of mobile targets with a team of robots. We show how to employ the probability hypothesis density filter to simultaneously estimate the number of targets and their positions. Next, we present a greedy algorithm for assigning trajectories to the robots to allow them to actively track the targets. We prove that the greedy algorithm is a two-approximation for maximizing submodular tracking objective functions. We examine two such functions: the mutual information between the estimated target positions and future measurements from the robots and a new objective that maximizes the expected number of targets detected by the robot team. We provide extensive simulation evaluations to validate the performance of our data-driven motion model and to compare the behavior and tracking performance of robots using our objective functions.

Keywords

Autonomous agents path planning for multiple mobile robot systems sensor fusion surveillance systems

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References

Adams

Mahler

(eds) (2014) Advances in probabilistic modeling: Applications of stochastic geometry. IEEE Robotics and Automation Magazine 21(2).

Atanasov

Le Ny

Daniilidis

et al . (2015) Decentralized active information acquisition: Theory and application to multi-robot slam. In: Proceedings of the IEEE International Conference on Robotics and Automation. Seattle, WA, USA, 26–30 May 2015.

Atanasov

Zhu

Daniilidis

et al . (2016) Localization from semantic observations via the matrix permanent. International Journal of Robotics Research 35(1–3): 73–99.

Calinescu

Chekuri

Pál

et al . (2007) Maximizing a submodular set function subject to a matroid constraint. In: Integer Programming and Combinatorial Optimization. Berlin, Heidelberg: Springer, pp.182–196.

Charrow

Michael

Kumar

(2015) Active control strategies for discovering and localizing devices with range-only sensors. In: Algorithmic foundation of robotics XI, pp. 55–71. Springer International Publishing.

Chung

Hollinger

Isler

(2011) Search and pursuit-evasion in mobile robotics. Autonomous Robots 31(4): 299–316.

Cover

Thomas

(2012) Elements of Information Theory. Hoboken, NJ: John Wiley & Sons.

Dames

Kumar

(2015) Autonomous localization of an unknown number of targets without data association using teams of mobile sensors. IEEE Transactions on Automation Science and Engineering 12(3): 850–864.

Dames

Tokekar

Kumar

(2015) Detecting, localizing, and tracking an unknown number of moving targets using a team of mobile robots. In: Proceedings of the international symposium on robotics research, Sestri Levante, Italy, 12–15 September 2015. Available at: https://www.springer.com/us/book/9783319515311 .

10.

Frew

Rock

(2003) Trajectory generation for constant velocity target motion estimation using monocular vision. In: Proceedings of the IEEE international conference on robotics and automation, Taipei, Taiwan, 14–19 September 2003, pp.3479–3484.

11.

Furukawa

Bourgault

Lavis

et al . (2006) Recursive Bayesian search-and-tracking using coordinated UAVs for lost targets. In: Proceedings of the IEEE international conference on robotics and automation, Orlando, FL, USA, 15–19 May 2006, pp.2521–2526.

12.

Gans

Nagarajan

et al . (2011) Keeping multiple moving targets in the field of view of a mobile camera. IEEE Transactions on Robotics 27(4): 822–828.

13.

Grabner

Nguyen

Gruber

et al . (2008) On-line boosting-based car detection from aerial images. ISPRS Journal of Photogrammetry and Remote Sensing 63(3): 382–396.

14.

Grocholsky

Keller

Kumar

et al . (2006) Cooperative air and ground surveillance. IEEE Robotics and Automation Magazine 13(3): 16–25.

15.

Hollinger

Djugash

Singh

(2012) Target tracking without line of sight using range from radio. Autonomous Robots 32(1): 1–14.

16.

Joseph

Doshi-Velez

Huang

et al . (2011) A Bayesian nonparametric approach to modeling motion patterns. Autonomous Robots 31(4): 383–400.

17.

Kim

Song

et al . (2014) Cooperative search of multiple unknown transient radio sources using multiple paired mobile robots. IEEE Transactions on Robotics 30(5): 1161–1173.

18.

Kotz

Henderson

(2005) CRAWDAD: A community resource for archiving wireless data at Dartmouth. IEEE Pervasive Computing 4(4): 12–14.

19.

Krause

Guestrin

(2005) Near-optimal sensor placements in Gaussian processes. In: Proceedings of the international conference on machine learning, Bonn, Germany, 7–11 August 2005.

20.

Kreucher

Kastella

Hero

III AO

(2005) Sensor management using an active sensing approach. Signal Processing 85(3): 607–624.

21.

Leung

Inostroza

Adams

(2014) Evaluating set measurement likelihoods in random-finite-set SLAM. In: IEEE international conference on information fusion, Salamanca, Spain, 7–10 July 2014, pp.1–8.

22.

Liang

et al . (2011) Smart community: An internet of things application. IEEE Communications Magazine 49(11): 68–75.

23.

Jilkov

(2003) Survey of maneuvering target tracking. Part I. Dynamic models. IEEE Transactions on Aerospace and Electronic Systems 39(4): 1333–1364.

24.

Jilkov

(2005) Survey of maneuvering target tracking. Part V. Multiple-model methods. IEEE Transactions on Aerospace and Electronic Systems 41(4): 1255–1321.

25.

Logothetis

Isaksson

Evans

(1997) An information theoretic approach to observer path design for bearings-only tracking. In: IEEE international conference on decision and control, San Diego, CA, USA, 10–12 December 1997, vol.4, pp.3132–3137.

26.

Mahler

(2003a) Multitarget bayes filtering via first-order multitarget moments. IEEE Transactions on Aerospace and Electronic Systems 39(4): 1152–1178.

27.

Mahler

(2003b) Objective functions for Bayesian control-theoretic sensor management, 1: Multitarget first-moment approximation. In: IEEE aerospace conference proceedings, vol.4. Big Sky, MT, USA, 8–15 March 2003.

28.

Mahler

(2007) Statistical Multisource–Multitarget Information Fusion, Boston: Artech House.

29.

Piorkowski

Sarafijanovic-Djukic

Grossglauser

(2009) CRAWDAD data set epfl/mobility (v. 2009-02-24). Downloaded from http://crawdad.org/epfl/mobility/.

30.

Rasmussen

Williams

(2006) Gaussian Processes for Machine Learning. Cambridge, MA, USA: MIT Press.

31.

Reuter

et al . (2014) The labeled multi-Bernoulli filter. IEEE Transactions on Signal Processing 62(12): 3246–3260.

32.

Ristic

Clark

(2010) Improved SMC implementation of the PHD filter. In: IEEE International Conference on Information Fusion. IEEE, pp.1–8.

33.

Ristic

Clark

(2011) A note on the reward function for PHD filters with sensor control. IEEE Transactions on Aerospace and Electronic Systems 47(2): 1521–1529.

34.

Song

Kim

(2012) Simultaneous localization of multiple unknown and transient radio sources using a mobile robot. IEEE Transactions on Robotics 28(3): 668–680.

35.

Spletzer

Taylor

(2003) Dynamic sensor planning and control for optimally tracking targets. International Journal of Robotics Research 22(1): 7–20.

36.

Stone

Streit

Corwin

et al . (2013) Bayesian Multiple Target Tracking. Boston, MA, USA: Artech House.

37.

Thrun

Burgard

Fox

(2005) Probabilistic Robotics. Cambridge, MA, USA: MIT Press.

38.

Tokekar

Branson

Vander Hook

et al . (2013) Tracking aquatic invaders: Autonomous robots for monitoring invasive fish. IEEE Robotics and Automation Magazine 20(3): 33–41.

39.

Tokekar

Isler

Franchi

(2014) Multi-target visual tracking with aerial robots. In: IEEE/RSJ international conference on intelligent robots and systems, Chicago, IL, USA, 14–18 September 2014, pp.3067–3072.

40.

Singh

Doucet

(2005) Sequential Monte Carlo methods for multi-target filtering with random finite sets. IEEE Transactions on Aerospace and Electronic Systems 41(4): 1224–1245.

41.

Fitch

Underwood

et al . (2013) Decentralized coordinated tracking with mixed discrete–continuous decisions. Journal of Field Robotics 30(5): 717–740.

42.

Zhao

Nevatia

(2003) Car detection in low resolution aerial images. Image and Vision Computing 21(8): 693–703.

43.

Zhou

Roumeliotis

(2008) Optimal motion strategies for range-only constrained multisensor target tracking. IEEE Transactions on Robotics 24(5): 1168–1185.

44.

Zhou

Roumeliotis

(2011) Multirobot active target tracking with combinations of relative observations. IEEE Transactions on Robotics 27(4): 678–695.

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