Skip to main content
Log in

A development platform for behavioral flexibility in autonomous unmanned aerial systems

  • Regular Paper
  • Published:
International Journal of Intelligent Robotics and Applications Aims and scope Submit manuscript

Abstract

Autonomous unmanned aerial systems (UAS) could supplement and eventually subsume a substantial portion of the mission set currently executed by remote pilots, making UAS more robust, responsive, and numerous than can be achieved by teleoperation alone. Unfortunately, the development of robust autonomous systems is difficult, costly, and time-consuming. Furthermore, the resulting systems often make little reuse of proven software components and offer limited adaptability for new tasks. This work presents a development platform for UAS which promotes behavioral flexibility. The platform incorporates the unified behavior framework (a modular, extensible autonomy framework), the robotic operating system (a robotic software framework), and PX4 (an open-source flight controller). Simulation of UBF agents identify a combination of reactive robotic control strategies effective for small-scale navigation tasks by a UAS in the presence of obstacles. Finally, flight tests provide a partial validation of the simulated results. The development platform presented in this work offers robust and responsive behavioral flexibility for UAS agents in simulation and reality using a methodology originally proven on ground robots.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

Notes

  1. www.dji.com.

  2. The multirotor simulation model was the Gazebo Iris Quadrotor: https://dev.px4.io/v1.9.0/en/airframes/airframe_reference.html#copter_quadrotor_wide_3dr_iris_quadrotor.

  3. https://dev.px4.io/master/en/simulation/ros_interface.html.

References

  • Arkin, R.C.: Motor schema-based mobile robot navigation. Int. J. Robot. Res. 8(4), 92–112 (1989)

    Article  MathSciNet  Google Scholar 

  • Beard, R.W., Mclain, T.W.: Implementing Dubins airplane paths on fixed-wing UAVs. In: Handbook for Unmanned Aerial Vehicles. Springer (2013)

  • Benjamin, M.R., Defilippo, M., Robinette, P., Novitzky, M.: Obstacle avoidance using multiobjective optimization and a dynamic obstacle manager. IEEE J. Ocean. Eng. 44(2), 331–342 (2019)

    Article  Google Scholar 

  • Brooks, R.: A robust layered control system for a mobile robot. IEEE J. Robot. Autom. 2(1), 14–23 (1986) [Online]. http://ieeexplore.ieee.org/document/1087032/

  • DODUAS.: Department of Defense Unmanned Aircraft Systems [Online] (2019). https://www.defense.gov/UAS/

  • Ebeid, E., Skriver, M., Terkildsen, K.H., Jensen, K., Schultz, U.P.: A survey of open-source UAV flight controllers and flight simulators. Microprocess. Microsyst. 61, 11–20 (2018) [Online]. http://www.sciencedirect.com/science/article/pii/S0141933118300930

  • Endsley, M.R.: Autonomous Horizons: System Autonomy in the Air Force—A Path to the Future. USAF, Tech. Rep. (2015)

  • Fisher, C.R.: Telewarfare and Military Medicine White Paper/State of the Art Report On AFMS Support to the Emerging Paradigm of Employed-in-Place Operations. AFMS, Tech. Rep. [Online] (2011). http://www.dtic.mil/dtic/tr/fulltext/u2/a593004.pdf

  • Gamma, E.: Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley, Boston (1995)

    Google Scholar 

  • Gat, E., Murphy, R.: On three-layer architectures. In: Artificial Intelligence and Mobile Robots, pp. 195–210. AAAI Press (1997)

  • Gupta, S.G., Ghonge, M.M., Jawandhiya, P.M.: Review of unmanned aircraft system (UAS). Int. J. Adv. Res. Comput. Eng. Technol. 2(4), 5 (2013)

    Google Scholar 

  • Hardison, C.M., Aharoni, E., Larson, C., Trochlil, S., Hou, A.C.: Stress and Dissatisfaction in the Air Force’s Remotely Piloted Aircraft Community: Focus Group Findings. Rand Corporation, Tech. Rep. (2017)

  • Huang, A.S., Olson, E., Moore, D.C.: LCM: Lightweight communications and marshalling. In: IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010, pp. 4057–4062 (2010)

  • Ippolito, C.A., Krishnakumar, K.S., Stepanyan, V., Bencomo, A., Chakrabarty, A., Hening, S.: An autonomy architecture concept for high-density operations of small UAS in urban environments. In: AIAA Scitech 2019 Forum (2019) [Online]. https://arc.aiaa.org/doi/abs/10.2514/6.2019-0689

  • Kaelbling, L.P.: An architecture for intelligent reactive systems. In: Reasoning About Actions & Plans, pp. 395–410. Elsevier (1987)

  • Kamrud, A.J., Hodson, D.D., Peterson, G.L., Woolley, B.G.: Unified behavior framework in discrete event simulation systems. J. Def. Model. Simul. 14(4), 471–481 (2017). https://doi.org/10.1177/1548512916683450. (online)

    Article  Google Scholar 

  • Kernel, H.: Odroid-XU4 (2019) [Online]. https://www.hardkernel.com/shop/odroid-xu4-special-price/

  • Less’ard-Springett, J., Friebe, A., Le Gallic, M.: Voter based control system for collision avoidance and sailboat navigation. In: Øvergård, K.I. (ed.) Robotic Sailing 2017, pp. 57–68. Springer International Publishing, Cham (2018)

    Chapter  Google Scholar 

  • Lowry, M., Bajwa, A.R., Pressburger, T., Sweet, A., Dalal, M., Fry, C., Schumann, J., Dahl, D., Karsa, G., Mahadevan, N.: Design considerations for a variable autonomy exeuctive for UAS in the NAS. In: 2018 AIAA Information Systems-AIAA Infotech @ Aerospace (2018) [Online]. https://arc.aiaa.org/doi/abs/10.2514/6.2018-1633

  • Maes, P.: Situated agents can have goals. Robot. Autonom. Syst. 6(1–2), 49–70 (1990)

    Article  Google Scholar 

  • Meier, L., Honegger, D., Pollefeys, M.: PX4: a node-based multithreaded open source robotics framework for deeply embedded platforms. In: 2015 IEEE International Conference on Robotics and Automation, pp. 6235–6240 (2015)

  • Murphy, R.R.: AI Robotics. MIT Press, Cambridge (2000)

    Google Scholar 

  • Oder, T.: The Dimensions of Russian Sea Denial in the Baltic Sea, Center for International Maritime Security, 1. [Online] (2018). http://cimsec.org/dimensions-russian-sea-denial-baltic-sea/35157

  • Peterson, S., Faramarzi, P.: Exclusive: Iran hijacked US drone, says Iranian engineer, The Christian Science Monitor (2011) [Online]. https://www.csmonitor.com/World/Middle-East/2011/1215/Exclusive-Iran-hijacked-US-drone-says-Iranian-engineer

  • Peterson, G.L., Duffy, J.P., Hooper, D.J.: Dynamic behavior sequencing for hybrid robot architectures. J. Intell. Robot. Syst. Theory Appl. 64(2), 179–196 (2011)

    Article  Google Scholar 

  • Pixhawk Hardware.: Pixhawk Autopilot (2019) [Online]. https://pixhawk.org/modules/pixhawk

  • Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Berger, E., Wheeler, R., Mg, A.: ROS: an open-source robot operating system. Icra 3(Figure 1), 5 (2009)

    Google Scholar 

  • Rasmussen, S., Kingston, D., Humphrey, L.R.: A brief introduction to unmanned systems autonomy services (UxAS). In: 2018 international conference on unmanned aircraft systems (ICUAS), pp. 257–268 (2018)

  • ROS.: ROS Documentation (2017) [Online]. http://wiki.ros.org/

  • Roberson, D., Hodson, D., Peterson, G., Woolley, B.: The unified behavior framework for the simulation of autonomous agents. In: Proceedings of the International Conference on Scientific Computing, pp. 49–58 (2015) [Online]. http://worldcomp-proceedings.com/proc/p2015/CSC7055.pdf

  • Rosenblatt, J.K.: DAMN: a distributed architecture for mobile navigation. J. Exp. Theor. Artif. Intell. 9(2–3), 339–360 (1997)

    Article  Google Scholar 

  • Tsardoulias, E., Mitkas, P.: Robotic frameworks, architectures and middleware comparison (2017) [Online]. arxiv:1711.06842

  • Woolley, B.G., Peterson, G.L.: Unified behavior framework for reactive robot control. J. Intell. Robot. Syst. Theory Appl. 55(2–3), 155–176 (2009) [Online]. http://link.springer.com/10.1007/s10846-008-9299-1

Download references

Acknowledgements

The views expressed in this document are those of the authors and do not reflect the official policy or position of the United States Air Force, the United States Department of Defense, or the United States Government.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Robert C. Leishman.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bodin, T.B., Bindewald, J.M., Leishman, R.C. et al. A development platform for behavioral flexibility in autonomous unmanned aerial systems. Int J Intell Robot Appl 4, 57–72 (2020). https://doi.org/10.1007/s41315-020-00120-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41315-020-00120-9

Keywords

Navigation