Kinodynamic planning for a fixed-wing aircraft in dynamic, cluttered environments : a local planning method using implicitly-defined motion primitives
Edwe Gerrit Cowley · SUNScholar (Stellenbosch University) · 2013
ENGLISH ABSTRACT: In order to navigate dynamic, cluttered environments safely, fully autonomous Unmanned Aerial Vehicles (UAVs) are required to plan conflict-free trajectories between two states in position-time space efficiently and reliably. Kinodynamic planning for vehicles with non-holonomic dynamic constraints is an NP-hard problem which is usually addressed using sampling-based, probabilistically complete motion planning algorithms. These algorithms are often applied in conjunction with a finite set of simple geometric motion primitives which encapsulate the dynamic constraints of the vehicle. This ensures that composite trajectories generated by the planning algorithm adhere to the vehicle dynamics. For many vehicles, accurate tracking of position-based trajectories is a non-trivial problem which demands complicated control techniques with high energy requirements. In an effort to reduce control complexity and thus also energy consumption, a generic Local Planning Method (LPM), able to plan trajectories based on implicitly-defined motion primitives, is developed in this project. This allows the planning algorithm to construct trajectories which are based on simulated results of vehicle motion under the control of a rudimentary auto-pilot, as opposed to a more complicated position-tracking system. The LPM abstracts motion primitives in such a way that it may theoretically be made applicable to various vehicles and control systems through simple substitution of the motion primitive set. The LPM, which is based on a variation of the Levenberg-Marquardt Algorithm (LMA), is integrated into a well-known Probabilistic Roadmap (PRM) kinodynamic planning algorithm which is known to work well in dynamic and cluttered environments. The complete motion planning algorithm is tested thoroughly in various simulated environments, using a vehicle model and controllers which have been previously verified against a real UAV during practical flight tests.