IDrone: Robust Drone Identification through Motion Actuation Feedback

Abstract

Swarms of Unmanned Aerial Vehicles (drones) could provide great benefit when used for disaster response and indoor search and rescue scenarios. In these harsh environments where GPS availability cannot be ensured, prior work often relies on cameras for control and localization. This creates the challenge of identifying each drone, i.e., finding the association between each physical ID (such as their radio address) and their visual ID (such as an object tracker output). To address this problem, prior work relies on visual cues such as LEDs or colored markers to provide unique information for identification. However, these methods often increase deployment difficulty, are sensitive to environmental changes, not robust to distance and might require hardware changes.

In this paper, we present IDrone, a robust physical drone identification system through motion matching and actuation feedback. The intuition is to (1) identify each drone by matching the motion detected through their inertial sensors and from an external camera, and (2) control the drones so they move in unique patterns that allow for fast identification, while minimizing the risk of collision involved in controlling drones with uncertain identification. To validate our approach, we conduct both simulation and real experimentation with autonomous drones for the simplified case of a stationary Spotter (powerful drone equipped with the camera). Overall, our initial results show that our approach offers a great tradeoff between fast identification and small collision probability. In particular, IDrone achieves faster identification time than safety-based baseline actuation (one-at-a-time), and significantly higher survival rate compared to fast, non-safety-based baseline actuation (random motion).

References

1. Jude Allred, Ahmad Bilal Hasan, Saroch Panichsakul, William Pisano, Peter Gray, Jyh Huang, Richard Han, Dale Lawrence, and Kamran Mohseni. 2007. SensorFlock: an airborne wireless sensor network of micro-air vehicles. In Proceedings of the 5th international conference on Embedded networked sensor systems - SenSys '07. ACM, 117--129.
2. H Bendea, Piero Boccardo, S Dequal, Fabio Giulio Tonolo, Davide Marenchino, and Marco Piras. 2008. Low cost UAV for post-disaster assessment. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 37, B8 (2008), 1373--1379.
3. Bret Bethke, Mario Valenti, and Jonathan How. 2007. Cooperative vision based estimation and tracking using multiple UAVs. In Advances in Cooperative Control and Optimization. Springer, 179--189.
4. Bitcraze. {n. d.}. CrazyFlie 2.0. https://www.bitcraze.io/crazyflie-2/. Accessed: 2016-08-19.
5. Angie Chandler, Joe Finney, Carl Lewis, and Alan Dix. 2009. Toward Emergent Technology for Blended Public Displays. In Proceedings of the 11th International Conference on Ubiquitous Computing. ACM, 101--104.
6. Chihway Chang, Christian Monstein, Alexandre Refregier, Adam Amara, Adrian Glauser, and Sarah Casura. 2015. Beam calibration of radio telescopes with drones. Publications of the Astronomical Society of the Pacific 127, 957 (2015), 1131.
7. Xinlei Chen, Aveek Purohit, Carlos Ruiz, Stefano Carpin, and Pei Zhang. 2015. DrunkWalk: Collaborative and Adaptive Planning for Navigation of Micro-Aerial Sensor Swarms. In Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems. ACM, 295--308.
8. Eric Cheng. 2015. Aerial photography and videography using drones. Peachpit Press.
9. Christopher Clarke, Alessio Bellino, Augusto Esteves, and Hans Gellersen. 2017. Remote Control by Body Movement in Synchrony with Orbiting Widgets: an Evaluation of TraceMatch. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (2017), 45.
10. Jean-Daniel Fekete, Niklas Elmqvist, and Yves Guiard. 2009. Motion-pointing: target selection using elliptical motions. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 289--298.
11. Markus Hehn, Robin Ritz, and Raffaello D'Andrea. 2012. Performance benchmarking of quadrotor systems using time-optimal control. Autonomous Robots 33, 1--2 (2012), 69--88.
12. Jonathan P How, Brett Behihke, Adrian Frank, Daniel Dale, and John Vian. 2008. Real-time indoor autonomous vehicle test environment. IEEE control systems 28, 2 (2008), 51--64.
13. Chitra R Karanam and Yasamin Mosto. 2017. 3D through-wall imaging with unmanned aerial vehicles using wifi. In Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks. ACM, 131--142.
14. Harold W Kuhn. 1955. The Hungarian method for the assignment problem. Naval research logistics quarterly 2, 1--2 (1955), 83--97.
15. Jason Tze Wah Lam. 2017. Three Axis Gimbals Stabilized Action Camera Lens Unit. US Patent App. 15/359,612.
16. Rene Mayrhofer and Hans Gellersen. 2009. Shake well before use: Intuitive and secure pairing of mobile devices. IEEE Transactions on Mobile Computing 8, 6 (2009), 792--806.
17. Nathan Michael, Daniel Mellinger, Quentin Lindsey, and Vijay Kumar. 2010. The grasp multiple micro-uav testbed. IEEE Robotics 8 Automation Magazine 17, 3 (2010), 56--65.
18. Mark W Mueller, Michael Hamer, and Raffaello D'Andrea. 2015. Fusing ultra-wideband range measurements with accelerometers and rate gyroscopes for quadrocopter state estimation. In Robotics and Automation (ICRA), 2015 IEEE International Conference on. IEEE, 1730--1736.
19. James Munkres. 1957. Algorithms for the assignment and transportation problems. Journal of the society for industrial and applied mathematics 5, 1 (1957), 32--38.
20. Katta G Murty. 1968. Letter to the editor---An algorithm for ranking all the assignments in order of increasing cost. Operations research 16, 3 (1968), 682--687.
21. Le T Nguyen, Yu Seung Kim, Patrick Tague, and Joy Zhang. 2014. IdentityLink: User-Device Linking through Visual and RF-Signal Cues. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp '14 Adjunct. ACM Press, New York, New York, USA, 529--539.
22. Shijia Pan, Carlos Ruiz, Jun Han, Adeola Bannis, Patrick Tague, Hae Young Noh, and Pei Zhang. 2018. UniverSense: IoT Device Pairing Through Heterogeneous Sensing Signals. In Proceedings of the 19th International Workshop on Mobile Computing Systems & Applications (HotMobile '18). ACM, New York, NY, USA, 55--60.
23. Shwetak N Patel, Jeffrey S Pierce, and Gregory D Abowd. 2004. A gesture-based authentication scheme for untrusted public terminals. In Proceedings of the 17th annual ACM symposium on User interface software and technology. ACM, 157--160.
24. Marc Perlin and Miguel D Bustamante. 2016. A robust quantitative comparison criterion of two signals based on the Sobolev norm of their difference. Journal of Engineering Mathematics 101, 1 (2016), 115--124.
25. Aveek Purohit, Zheng Sun, Frank Mokaya, and Pei Zhang. 2011. SensorFly: Controlled-mobile sensing platform for indoor emergency response applications. In 10th International Conference on Information Processing in Sensor Networks (IPSN). IEEE, 223--234.
26. Markus Quaritsch, Robert Kuschnig, Hermann Hellwagner, Bernhard Rinner, A Adria, and U Klagenfurt. 2011. Fast aerial image acquisition and mosaicking for emergency response operations by collaborative UAVs. In Proceedings for the International ISCRAM Conference. 1--5.
27. Carlos Ruiz, Xinlei Chen, Lin Zhang, and Pei Zhang. 2016. Collaborative Localization and Navigation in Heterogeneous UAV swarms: Demo Abstract. In Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM. ACM, 324--325.
28. Lucas Vago Santana, Alexandre Santos Brandao, Mario Sarcinelli-Filho, and Ricardo Carelli. 2014. A trajectory tracking and 3d positioning controller for the ar. drone quadrotor. In Unmanned Aircraft Systems (ICUAS), 2014 International Conference on. IEEE, 756--767.
29. Abraham Savitzky and Marcel JE Golay. 1964. Smoothing and differentiation of data by simplified least squares procedures. Analytical chemistry 36, 8 (1964), 1627--1639.
30. Zheng Sun, Aveek Purohit, Raja Bose, and Pei Zhang. 2013. Spartacus: spatially-aware interaction for mobile devices through energy-efficient audio sensing. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services. ACM, 263--276.
31. Thiago Teixeira, Deokwoo Jung, and Andreas Savvides. 2010. Tasking networked cctv cameras and mobile phones to identify and localize multiple people. Proceedings of the 12th ACM ... (2010), 213--222.
32. Eduardo Velloso, Marcus Carter, Joshua Newn, Augusto Esteves, Christopher Clarke, and Hans Gellersen. 2017. Motion Correlation: Selecting Objects by Matching Their Movement. ACM Transactions on Computer-Human Interaction (TOCHI) 24, 3 (2017), 22.
33. Sonia Waharte and Niki Trigoni. 2010. Supporting search and rescue operations with UAVs. In International Conference on Emerging Security Technologies (EST). IEEE, 142--147.
34. John A Wallace. 2012. Integrating Unmanned Aircraft Systems Into Modern Policing in An Urban Environment. Technical Report. DTIC Document.
35. Luke Wallace, Arko Lucieer, Christopher Watson, and Darren Turner. 2012. Development of a UAV-LiDAR system with application to forest inventory. Remote Sensing 4, 6 (2012), 1519--1543.
36. John Williamson and Roderick Murray-Smith. 2004. Pointing without a pointer. In CHI'04 Extended Abstracts on Human Factors in Computing Systems. ACM, 1407--1410.
37. Andrew D Wilson and Hrvoje Benko. 2014. Crossmotion: fusing device and image motion for user identification, tracking and device association. In Proceedings of the 16th International Conference on Multimodal Interaction. ACM, 216--223.
38. Zhengyou Zhang. 2000. A flexible new technique for camera calibration. IEEE Transactions on pattern analysis and machine intelligence 22, 11 (2000), 1330--1334.

Index Terms

• Computing methodologies

  • Artificial intelligence

    • Computer vision

      • Computer vision problems

        • Matching

        • Object identification

        • Tracking