Optimal path planning for an aerial vehicle in 3D space

Hota, Sikha; Ghose, Debasish

doi:10.1109/cdc.2010.5717246

Cited by 42 publications

(36 citation statements)

References 18 publications

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“…Moreover, look-up tables are usually required, increasing the operational complexity. The second category can provide closed-form solutions, using, for example, B-splines, Bezier curves or spatial Pythagorean hodographs [23,24,25,27,28,29,30]. These curves are used for trajectory generation for both UAVs [23,24] and autonomous robots [25,28].…”

Section: Introductionmentioning

confidence: 99%

“…Generated paths have continuous curvature when using Bezier curves [31] or B-splines [32], but little attention has been given to the maximum curvature constraint. Although it has been demonstrated that curvature extrema can be obtained numerically for any planar cubic curve, this might be a challenge for parametric polynomial curves [29,33], since it is difficult to solve the formulated curvature extremum model. An objective function has been designed to search for proper Bezier curve parameters that satisfy the maximum curvature constraint, but the optimization problem remains unsolved [34].…”

Section: Introductionmentioning

confidence: 99%

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Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs

Wang

Jiang

et al. 2017

Sensors

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Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs

Wang

Jiang

et al. 2017

Sensors

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“…Sussman [8] discussed Dubins problem in 3D space to find that every minimizer is either a concatenation of three pieces, each of which is a straight line or circle, or a helicoidal arc. Based on Sussmann's result, optimal paths for 3D waypoint following problem are generated in [9], [10] and [11] considering the kinematic model of a MAV. Bottasso et al [12] considered a 3D sequence of waypoints connected by straight flight trim conditions as input, and smoothened it optimally to make it compatible with vehicle dynamics.…”

Section: Introductionmentioning

confidence: 99%

Optimal transition trajectory for waypoint following

Hota

Ghose

2013

2013 IEEE International Conference on Control Applications (CCA)

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This paper discusses the problem of a turn-rate constrained vehicle, such as a fixed-wing MAV (miniature air vehicle) required to fly along the path defined by a series of waypoints. An extremal path, named as γ-trajectory, that transitions between two consecutive waypoint segments (obtained by joining two waypoints in sequence) in a timeoptimal fashion, is obtained. This algorithm is also used to track the maximum portion of waypoint segments with the desired shortest distance between the trajectory and the associated waypoint. Subsequently, the proposed trajectory is compared with existing transition trajectory in the literature to show better performance in several aspects.

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“…This algorithm has been implemented on the UAV, and is only applicable when the distance between the initial and final positions onto the x-y plane is large. Hota and Ghose [26] employed a numerical method to obtain an optimal path meeting geometric constraints. However, this method could not be applied in dynamic trajectory smoothing because of time-consuming computation.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Dynamic Dubins-Helix Method for 3-D Trajectory Smoothing

Wang

Tan

et al. 2015

IEEE Trans. Contr. Syst. Technol.

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This brief presents the real-time dynamic Dubins-Helix (RDDH) method for trajectory smoothing, which consists of Dubins-Helix trajectory generation and pitch angle smoothing. The generated 3-D trajectory is called the RDDH trajectory. On one hand, the projection of 3-D trajectory on the horizontal plane is partially generated by Dubins path planner such that the curvature radius constraint is satisfied. On the other hand, the Helix curve is constructed to satisfy the pitch angle constraint, even in the case that the initial and final poses are close. Furthermore, by analyzing the relationship between the parameters and the effectiveness of the RDDH trajectory, the smoothing algorithm is designed to obtain appropriate parameters for a shorter and smoother trajectory. In the end, the numerical results show the proposed method can generate an effective trajectory under diverse initial conditions and achieve real-time computation.

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Optimal path planning for an aerial vehicle in 3D space

Cited by 42 publications

References 18 publications

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs

Optimal transition trajectory for waypoint following

Real-Time Dynamic Dubins-Helix Method for 3-D Trajectory Smoothing

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