An Online Motion Planning Method for UAV Based on Improved Fast Random Search Tree
A random search and motion planning technology, which is applied in the direction of finding the target control, can solve the problems of system online planning and control instability, and achieve the effect of improving node growth efficiency
Active Publication Date: 2020-09-15
TSINGHUA UNIV
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However, in the actual scene, the inevitable trajectory tracking deviation and the change of the environment make the planning problem often change and require continuous re-planning, while the sampling-based planning method will cause the shape and structure of the generated trajectory to change due to the randomness of sampling. It may eventually lead to instability in online planning and control of the entire system
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[0034] The present invention proposes a UAV online motion planning method based on an improved fast random search tree. The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0035] The present invention proposes an online motion planning method for UAVs based on improved fast random search tree, the overall process is as follows figure 1 As shown, it specifically includes the following steps:
[0036] 1) Set the length Δt of the planning cycle (usually set according to the map information update frequency, the length of this embodiment is 1s), and record the initial moment of each planning cycle as t time;
[0037] 2) Take the first planning cycle as the current planning cycle;
[0038] 3) At the initial moment of the current planning cycle, initialize the spanning tree as the current spanning tree; obtain the real-time pose state of the UAV (including the three-axis position, velocity, attitu...
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The invention proposes an unmanned aerial vehicle online motion planning method based on an improved random search tree and belongs to the field of motion planning of unmanned aerial vehicles. The method includes the following steps: when a first planning cycle comes, initializing a spanning tree taking a real-time posture state of an unmanned aerial vehicle as a root node and a feasible trajectory set; when each planning cycle comes, searching and determining, in a current spanning tree, a node which is the closest to an initial state of the unmanned aerial vehicle, and updating a root node of the current spanning tree; and pruning the current spanning tree according to the new root node, performing spanning tree growth during the remaining duration of the current planning cycle, and updating a current feasible trajectory set; and when each planning cycle ends, if a node corresponding to a real-time state of the unmanned aerial vehicle is connected to a feasible trajectory successfully, and the connected trajectory is feasible in an updated map, outputting the feasible trajectory. The unmanned aerial vehicle online motion planning method based on the improved random search tree improves the efficiency of an algorithm on the basis of guaranteeing the kinematic constraint and optimality of the output trajectory, optimizes the trajectory output stability, and enables the unmannedaerial vehicle to have the capability of autonomous flight in an actual scene.
Description
technical field [0001] The invention relates to an online motion planning method for an unmanned aerial vehicle based on an improved fast random search tree, and belongs to the field of unmanned aerial vehicle motion planning. Background technique [0002] The main goal of UAV online motion planning is to output continuous and stable reachable trajectories online based on the task of flying from the UAV's real-time state to the target state, according to the UAV's own motion constraints and online updated map information. Online motion planning is an important capability that UAVs must possess to perform tasks in actual scenarios, and it is also one of the key technologies to realize autonomous flight of UAVs. [0003] In actual scenarios where UAVs perform tasks, such as closed office spaces or factory environments, movable obstacles cause dynamic changes in environmental information, and the topology of spatial connectivity may also change. In addition, the unstructured a...
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IPC IPC(8): G05D1/12
CPCG05D1/12
Inventor 朱正达程农李清
Owner TSINGHUA UNIV