JZUS - Journal of Zhejiang University SCIENCE

Frontiers of Information Technology & Electronic Engineering 2019 Vol.20 No.1 P.107-119

Safe navigation of quadrotors with jerk limited trajectory

Author(s): Shu-peng Lai, Meng-lu Lan, Ya-xuan Li, Ben M. Chen
Affiliation(s): Department of Electrical and Computer Engineering, National University of Singapore, Singapore; more
Corresponding email(s): elelais@nus.edu.sg
Key Words: Quadrotor, Unmanned aerial vehicle, Motion planning

Share this article to： More <<< Previous Article \|Next Article >>>

Abstract: 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.

带状态饱和的四旋翼安全轨迹规划

摘要：当前，许多基于小型多旋翼的实际应用需考虑障碍物与安全条例的影响。在机载导航计算机有限计算能力下，实时生成安全并符合飞行器动力学特征与状态约束的轨迹，一直以来都是一项挑战。提出一种新型基于安全飞行走廊的轨迹规划方法。该方法可在10μs内，渐进规划出安全的飞行轨迹。本研究中，安全走廊基于可旋转的多个长方体搭建而成。所提方法已通过模拟和实机实验验证。

关键词：四旋翼飞行器；无人机；运动规划

Reference

[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.

[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.

[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.

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

[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.

[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.

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

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

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

[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.

[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.

[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.

[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.

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

[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.

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

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Similar articles

- Go to

带状态饱和的四旋翼安全轨迹规划

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference