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Safe navigation of quadrotors with jerk limited trajectory


Many aerial applications require unmanned aerial systems operate in safe zones because of the presence of obstacles or security regulations. It is a non-trivial task to generate a smooth trajectory satisfying both dynamic constraints and motion limits of the unmanned vehicles while being inside the safe zones. Then the task becomes even more challenging for real-time applications, for which computational efficiency is crucial. In this study, we present a safe flying corridor navigation method, which combines jerk limited trajectories with an efficient testing method to update the position setpoints in real time. Trajectories are generated online and incrementally with a cycle time smaller than 10 μs, which is exceptionally suitable for vehicles with limited onboard computational capability. Safe zones are represented with multiple interconnected bounding boxes which can be arbitrarily oriented. The jerk limited trajectory generation algorithm has been extended to cover the cases with asymmetrical motion limits. The proposed method has been successfully tested and verified in flight simulations and actual experiments.

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  1. Ang KZY, Dong XX, Liu WQ, et al., 2018. High-precision multi-UAV teaming for the first outdoor night show in Singapore. Unmanned Syst, 6(1):39–65.

    Article  Google Scholar 

  2. Chen J, Shen SJ, 2017. Improving octree-based occupancy maps using environment sparsity with application to aerial robot navigation. Proc IEEE Int Conf on Robotics and Automation, p.3656–3663.

    Google Scholar 

  3. Ezair B, Tassa T, Shiller Z, 2014. Planning high order trajectories with general initial and final conditions and asymmetric bounds. Int J Rob Res, 33(6):898–916.

    Article  Google Scholar 

  4. Florence P, Carter J, Tedrake R, 2016. Integrated perception and control at high speed: evaluating collision avoidance maneuvers without maps. Proc 12th Int Workshop on the Algorithmic Foundations of Robotics.

    Google Scholar 

  5. Gao F, Lin Y, Shen SJ, 2017. Gradient-based online safe trajectory generation for quadrotor flight in complex environments. Proc IEEE/RSJ Int Conf on Intelligent Robots and Systems, p.3681–3688.

    Google Scholar 

  6. Haschke R, Weitnauer E, Ritter H, 2008. On-line planning of time-optimal, jerk-limited trajectories. Proc IEEE/RSJ Int Conf on Intelligent Robots and Systems, p.3248–3253.

    Google Scholar 

  7. Hehn M, D’Andrea R, 2015. Real-time trajectory generation for quadrocopters. IEEE Trans Rob, 31(4):877–892.

    Article  Google Scholar 

  8. Kröger T, 2011. Opening the door to new sensor-based robot applications—the reflexxes motion libraries. Proc IEEE Int Conf on Robotics and Automation, p.1–4.

    Google Scholar 

  9. Kröger T, Wahl FM, 2010. Online trajectory generation: basic concepts for instantaneous reactions to unforeseen events. IEEE Trans Rob, 26(1):94–111.

    Article  Google Scholar 

  10. Lai SP, Wang KL, Qin HL, et al., 2016. A robust online path planning approach in cluttered environments for micro rotorcraft drones. Contr Theory Technol, 14(1):83–96.

    MathSciNet  Article  Google Scholar 

  11. Lai SP, Lan ML, Chen BM, 2018. Optimal constrained trajectory generation for quadrotors through smoothing splines. Proc IEEE/RSJ Int Conf on Intelligent Robots and Systems, p.4743–4750.

    Google Scholar 

  12. Liu SK, Watterson M, Mohta K, et al., 2017. Planning dynamically feasible trajectories for quadrotors using safe flight corridors in 3-D complex environments. IEEE Rob Autom Lett, 2(3):1688–1695.

    Article  Google Scholar 

  13. Lopez BT, How JP, 2017. Aggressive 3-D collision avoidance for high-speed navigation. Proc IEEE Int Conf on Robotics and Automation, p.5759–5765.

    Google Scholar 

  14. Peng KM, Lin F, Chen BM, 2017. Online schedule for autonomy of multiple unmanned aerial vehicles. Sci China Inform Sci, 60(7):072203.

    Article  Google Scholar 

  15. Ren M, Huo XH, 2010. Asynchronous double-precision windows based unmanned aerial vehicle real-time path planning. Sci China Inform Sci, 53(2):215–222.

    Article  Google Scholar 

  16. Wang KL, Ke YJ, Chen BM, 2017. Autonomous reconfigurable hybrid tail-sitter UAV U-Lion. Sci China Inform Sci, 60(3):033201.

    Article  Google Scholar 

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Correspondence to Shu-peng Lai.

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Lai, Sp., Lan, Ml., Li, Yx. et al. Safe navigation of quadrotors with jerk limited trajectory. Frontiers Inf Technol Electronic Eng 20, 107–119 (2019).

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Key words

  • Quadrotor
  • Unmanned aerial vehicle
  • Motion planning

CLC number

  • V279