Reactive route selection from pre-calculated trajectories – application to micro-UAV path planning

Operating micro-UAVs autonomously in complex urban areas requires that the guidance algorithms on-board are robust to changes in the operating environment. Limited endurance capability demands an optimal guidance algorithm, which will change as the environment does. All optimal path-planning routines are computationally intensive, with processor load a function of the environmental complexity. This paper presents a new algorithm, the reactive route selection algorithm, for storing a bank of optimal trajectories computed off-line and blending between these optimal trajectories as the operating environment changes. An example is presented using a mixed-integer linear program to generate the optimal trajectories.

[1]  S. LaValle.  Rapidly-exploring random trees : a new tool for path planning , 1998 .

[2]  Yang Wang,et al.  Fast Model Predictive Control Using Online Optimization , 2008 .

[3]  Scott A. Bortoff,et al.  Path planning for UAVs , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[4]  Anthony Stentz,et al.  The Delayed D* Algorithm for Efficient Path Replanning , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[5]  Jan Tommy Gravdahl,et al.  Modelling of UAV formation flight using 3D potential field , 2008, Simul. Model. Pract. Theory.

[6]  Alison Eele,et al.  Path Planning with Avoidance Using Nonlinear Branch-and-Bound , 2007 .

[7]  Brian R. Geiger,et al.  Optimal Path Planning of UAVs Using Direct Collocation with Nonlinear Programming , 2006 .

[8]  Semyon M. Meerkov,et al.  Optimal Path Planning for Unmanned Combat Aerial Vehicles to Defeat Radar Tracking , 2006 .

[9]  Nils J. Nilsson,et al.  Principles of Artificial Intelligence , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  E. Pistikopoulos,et al.  A new multiparametric mixed-integer quadratic programming algorithm , 2001 .

[11]  B. Moor,et al.  Mixed integer programming for multi-vehicle path planning , 2001, 2001 European Control Conference (ECC).

[12]  Jonathan P. How,et al.  COORDINATION AND CONTROL OF MULTIPLE UAVs , 2002 .

[13]  Datta N. Godbole,et al.  Active multi-model control for dynamic maneuver optimization of unmanned air vehicles , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[14]  D. Rathbun,et al.  An evolution based path planning algorithm for autonomous motion of a UAV through uncertain environments , 2002, Proceedings. The 21st Digital Avionics Systems Conference.

[15]  David Anderson,et al.  Fast Model Predictive Control of the Nadir Singularity in Electro-Optic Systems , 2009 .

[16]  B. Mettler,et al.  Nonlinear trajectory generation for autonomous vehicles via parameterized maneuver classes , 2006 .

[17]  Alberto Bemporad,et al.  The explicit linear quadratic regulator for constrained systems , 2003, Autom..

[18]  Stephen P. Boyd,et al.  Fast Model Predictive Control Using Online Optimization , 2010, IEEE Transactions on Control Systems Technology.