Abstract
Abstract This study presents a novel methodology for generating smooth feasible paths for autonomous aerial vehicles in the three-dimensional space based on a variation of the Spatial Quintic Pythagorean Hodographs curves. Generated paths must satisfy three main constraints: (i) maximum curvature, (ii) maximum torsion and (iii) maximum climb (or dive) angle. A given path is considered to be feasible if the main kinematic constraints of the vehicle are not violated, which is accomplished in our approach by connecting different waypoints with seventh order Bézier curves. This also indirectly insures the smoothness of the vehicle’s acceleration profile between two consecutive points of the curve and of the entire path by controlling the curvature values at the extreme points of each composing Bézier curve segment. The computation of the Pythagorean Hodograph is cast as an optimization problem, for which we provide an algorithm with fast convergence to the final result. The proposed methodology is applicable to vehicles in three-dimensional environments, which can be modeled presuming the imposed constraints. Our methodology is validated in simulation with real parameters and simulated flight data of a small autonomous aerial vehicle.
Highlights
Path planning is a fundamental task for any kind of autonomous mobile robot
As far as the capacity of covering a broad set of relevant applications is concerned, Unmanned Aerial Vehicles (UAVs) clearly have their niche of applications, which cannot be fulfilled by other types of mobile robots
The method takes into account three major motion constraints of a fixed-wing UAV in the threedimensional space: maximum curvature, maximum torsion and maximum climb angle, but with special emphasis on the cases of limited climb rates
Summary
Path planning is a fundamental task for any kind of autonomous mobile robot. Even though it might be possible for such robots to traverse their environments solely in a reactive way, the competence of planning and computing paths is an important feature for a large number of vehicles and a great variety of tasks. Less obvious, the increased freedom provided by a less restrictive environment poses many new challenges Current problems, such as path planning for multiple Unmanned Aerial Vehicles (UAVs) and Autonomous Underwater Vehicles (AUVs), still call for better solutions. As far as the capacity of covering a broad set of relevant applications is concerned, UAVs clearly have their niche of applications, which cannot be fulfilled by other types of mobile robots One of their main advantages is in several types of monitoring and surveillance tasks, where they are able to navigate over large areas obviously faster than land vehicles, with a privileged view from above. Curvature radius is one such restriction imposed on paths generated for typical Ackerman steering vehicles, since the sliding constraint of wheels dictates that the component of the wheel’s motion orthogonal to the wheel plane must be zero
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