Real-time 3D Route Planning based on Modified Rapidly Exploring Random-tree Algorithm

Zhang, Shaoqing; Lv, Mingwei; Yang, Chen

doi:10.1109/iceict.2019.8846357

Cited by 2 publications

(2 citation statements)

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“…In the literature two distinct approaches are being used to reduce the complexity of the environment space. First, the bounds of the environments problem space are defined, serving to constrain the environment to a fixed area, which may range from several meters [48][49][50], to several kilometres [51][52][53]. Second, the frame of reference system applied to the environment is simplified away from a geographic coordinate system (degrees of latitude/longitude) to an abstract coordinate system in which the origin, orientation and the scale of the reference frame can be defined by the user in problem simulations.…”

Section: Uav Positioning Within An Environmentmentioning

confidence: 99%

“…Whilst parameters can be modified to dictate the placement of tree nodes and ultimately used to define the explorative nature of RRT algorithms, paths are consistently formed from origin until a destination is reached. Applied from the opposite direction (i.e., destination to origin) [49] presents a Modified-RRT (M-RRT) pathplanning solution, employing a reverse path search conducted across an existing RRT three dimensional tree structure. Applied as a greedy strategy, M-RRT has achieved good real-time performance and proven its ability to solve real-time 3D route problems.…”

Section: Uav Path-planning Approachesmentioning

confidence: 99%

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Path-Planning for Unmanned Aerial Vehicles with Environment Complexity Considerations: A Survey

2023

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Unmanned aerial vehicles (UAVs) have the potential to make a significant impact in a range of scenarios where it is too risky or too costly to rely on human labour. Fleets of autonomous UAVs, which complete tasks collaboratively while managing their basic flight and related tasks independently, present further opportunities along with research and regulatory challenges. Improvements in UAV construction and components, along with developments in embedded computing hardware, communication mechanisms and sensors which may be mounted on-board a UAV are nearing the point where commercial deployment of fleets of autonomous UAVs will be technically possible. To fulfil this potential, UAVs will need to operate safely and reliably in complex and potentially dynamically changing environments with path-planning, obstacle sensing and collision avoidance paramount. This survey presents an original environment complexity classification, and critically analyses the current state of the art in relation to UAV path-planning approaches. Moreover, it highlights the existing challenges in environment complexity modelling and representation, path-planning approaches, and outlines open research questions together with future directions.

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