Collision Avoidance of Fixed-Wing UAVs in Dynamic Environments Based on Spline-RRT and Velocity Obstacle

It is crucial to online plan a smooth, continuous and collision-free path to navigate a fixed-wing unmanned aircraft through complex environments. In a static environment, given priori knowledge of the map, the sampling-based RRT (rapidly exploring random tree) method and its variants are efficient to provide global path planning to navigate the fixed-wing aircraft through static obstacles. However, in complex and dynamic situations, the fixed-wing aircraft may encounter dynamic obstacles when following the planned global path. In the presence of dynamic obstacles within the sensing range of the fixed-wing aircraft, it is challenging to on-line generate a new collision-free and smooth path. In this paper, a real-time collision-free path planning strategy is proposed for fixed-wing aircraft in dynamic environments. Specifically, the proposed collision-free path planner named as Spline-RRT-VO is presented incorporating the spline-RRT algorithm and the velocity obstacle (VO) method to avoid a high-speed dynamic obstacle. In the proposed spline-RRT-VO approach, a random tree grows in the local area, meanwhile, the VO method is used to extend tree edges and reject unavailable nodes. It improves the tree growing in a more efficient and smooth manner. Simulation results verify the effectiveness of the spline-RRT-VO method to navigate the fixed-wing UAVs through dynamic environments.

[1]  Steven M. LaValle,et al.  RRT-connect: An efficient approach to single-query path planning , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[2]  Sebastian Benders Reconfigurable Path Planning for Fixed-wing Unmanned Aircraft Using Free-Space Roadmaps , 2018, 2018 International Conference on Unmanned Aircraft Systems (ICUAS).

[3]  David Hyunchul Shim,et al.  Path planner based on bidirectional spline-RRT∗ for fixed-wing UAVs , 2016, 2016 International Conference on Unmanned Aircraft Systems (ICUAS).

[4]  Hui Cheng,et al.  Avoidance of High-Speed Obstacles Based on Velocity Obstacles , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[5]  Sangwoo Moon,et al.  Spline-Based RRT Path Planner for Non-Holonomic Robots , 2013, Journal of Intelligent & Robotic Systems.

[6]  Paolo Fiorini,et al.  Motion Planning in Dynamic Environments Using Velocity Obstacles , 1998, Int. J. Robotics Res..

[7]  Dave Eberly Testing for Intersection of Convex Objects: The Method of Separating Axes , 2001 .

[8]  Steven M. LaValle,et al.  Randomized Kinodynamic Planning , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[9]  Ian Postlethwaite,et al.  A Probabilistically Robust Path Planning Algorithm for UAVs Using Rapidly-Exploring Random Trees , 2013, J. Intell. Robotic Syst..

[10]  Timothy W. McLain,et al.  Small Unmanned Aircraft: Theory and Practice , 2012 .

[11]  Mani Shankar Prasad,et al.  Three dimensional D* algorithm for incremental path planning in uncooperative environment , 2016, 2016 3rd International Conference on Signal Processing and Integrated Networks (SPIN).

[12]  L. Dubins On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents , 1957 .

[13]  Panagiotis Tsiotras,et al.  Dynamic programming guided exploration for sampling-based motion planning algorithms , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[14]  Syeda Madiha Qamar,et al.  Potential guided directional-RRT* for accelerated motion planning in cluttered environments , 2013, 2013 IEEE International Conference on Mechatronics and Automation.

[15]  Siddhartha S. Srinivasa,et al.  Informed Sampling for Asymptotically Optimal Path Planning , 2018, IEEE Transactions on Robotics.

[16]  Dinesh Manocha,et al.  PORCA: Modeling and Planning for Autonomous Driving Among Many Pedestrians , 2018, IEEE Robotics and Automation Letters.

[17]  James J. Kuffner,et al.  Randomized statistical path planning , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Kourosh Naderi,et al.  RT-RRT*: a real-time path planning algorithm based on RRT* , 2015, MIG.

[19]  James McLurkin,et al.  The Extended Velocity Obstacle and applying ORCA in the real world , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[20]  Takeo Kanade,et al.  Efficient Two-phase 3D Motion Planning for Small Fixed-wing UAVs , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[21]  Jonathan P. How,et al.  Real-Time Motion Planning With Applications to Autonomous Urban Driving , 2009, IEEE Transactions on Control Systems Technology.

[22]  Dinesh Manocha,et al.  Reciprocal n-Body Collision Avoidance , 2011, ISRR.

[23]  Dinesh Manocha,et al.  Smooth and collision-free navigation for multiple robots under differential-drive constraints , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[24]  Hung Manh La,et al.  Dynamic path planning and replanning for mobile robots using RRT , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[25]  Simon Schopferer,et al.  Performance-aware flight path planning for unmanned aircraft in uniform wind fields , 2015, 2015 International Conference on Unmanned Aircraft Systems (ICUAS).

[26]  Jia Li,et al.  Real-time obstacle avoidance for fixed-wing vehicles in complex environment , 2016, 2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC).

[27]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[28]  Emilio Frazzoli,et al.  Sampling-based algorithms for optimal motion planning , 2011, Int. J. Robotics Res..

[29]  Paul A. Beardsley,et al.  Collision avoidance for aerial vehicles in multi-agent scenarios , 2015, Auton. Robots.

[30]  Hui Cheng,et al.  Decentralized navigation of multiple agents based on ORCA and model predictive control , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[31]  Roland Siegwart,et al.  Optimal Reciprocal Collision Avoidance for Multiple Non-Holonomic Robots , 2013 .

[32]  Mehdi Tale Masouleh,et al.  An optimal motion planning and obstacle avoidance algorithm based on the finite time velocity obstacle approach , 2017, 2017 Artificial Intelligence and Signal Processing Conference (AISP).

[33]  Jur P. van den Berg,et al.  3-D Reciprocal Collision Avoidance on Physical Quadrotor Helicopters with On-Board Sensing for Relative Positioning , 2014, ArXiv.

[34]  Dinesh Manocha,et al.  Reciprocal Velocity Obstacles for real-time multi-agent navigation , 2008, 2008 IEEE International Conference on Robotics and Automation.

[35]  Florian-Michael Adolf,et al.  Multi-query Path Planning for an Unmanned Fixed-Wing Aircraft , 2013 .

[36]  Siddhartha S. Srinivasa,et al.  Informed RRT*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[37]  Yao Ma,et al.  Multi-UAVs Cooperative Path Planning Method based on Improved RRT Algorithm , 2018, 2018 IEEE International Conference on Mechatronics and Automation (ICMA).

[38]  Paul A. Beardsley,et al.  Optimal Reciprocal Collision Avoidance for Multiple Non-Holonomic Robots , 2010, DARS.

[39]  Steven M. LaValle,et al.  Rapidly-Exploring Random Trees: Progress and Prospects , 2000 .