Abstract
To improve the safety and effectiveness of autonomous towing aircraft aboard the carrier deck, this study proposes a velocity-restricted path planner algorithm named as kinodynamic safety optimal rapidly exploring random tree (KS-RRT ∗ ) to plan a near time-optimal path. First, a speed map is introduced to assign different maximum allowable velocity for the sampling points in the workspace, and the traverse time is calculated along the kinodynamic connection of two sampling points. Then the near time-optimal path in the tree-structured search map can be obtained by the rewiring procedures, instead of a distance-optimal path in the original RRT ∗ algorithm. In order to enhance the planner’s performance, goal biasing scheme and fast collision checking technique are adopted in the algorithm. Since the sampling-based methods are sensitive to their parameters, simulation experiments are first conducted to determine the optimal input settings for the specific problem. The effectiveness of the proposed algorithm is validated in several common aircraft parking scenarios. Comparing with standard RRT ∗ and human heuristic driving, KS-RRT ∗ demonstrates a higher success rate, as well as shorter computation and trajectory time. In conclusion, KS-RRT ∗ algorithm is suitable to generate a near time-optimal safe path for autonomous high density parking in semistructured environment.
Highlights
Aircraft parking aboard the carrier deck is a carefully planned procedure in naval operations standardization [1], and its safety and effectiveness are essential in determining the sortie generation capacity of air wing [2]
The aircraft parking operation is usually manpower intensive and time-consuming evolution with low reliability, which creates a more hazard situation for the already congested deck environment leading to mishaps [3]. erefore, it is imperative to introduce an autonomous path planner that can speed up the aircraft parking operations with major improvements in safety and reduction in total manpower
Erefore, this study presents a variant of Rapidly random tree (RRT)∗, called Kinodynamic Safety RRT∗ (KS-RRT∗), which adopts a speed map to assign different reference safety velocities in the searching space and introduces a time-based metric to determine an optimal path for aircraft parking operation
Summary
Aircraft parking aboard the carrier deck is a carefully planned procedure in naval operations standardization [1], and its safety and effectiveness are essential in determining the sortie generation capacity of air wing [2]. Erefore, it is imperative to introduce an autonomous path planner that can speed up the aircraft parking operations with major improvements in safety and reduction in total manpower. The aircraft parking operation is usually manpower intensive and time-consuming evolution with low reliability, which creates a more hazard situation for the already congested deck environment leading to mishaps [3]. Path planning is both a kinematic and geometric problem that specifies a set of configurations from one place to another and avoids obstacles. Considerable efforts are devoted to solve this problem. e algorithms of graph searching methods [5,6,7] give a path solution by discretizing the state of workspace and visiting different states, while the state space is always so large that evaluating every potential solution is computational costly
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