Energy-Efficient Path Planning for UAV Using Spatiotemporal Wind Model

Aoki, Nobuaki; Ishigami, Genya

doi:10.7210/jrsj.40.255

Cited by 1 publication

(3 citation statements)

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“…While the usefulness of the energy-efficient global planner is shown in the previous work, 23 this paper verifies the planner using the high-fidelity simulator. The Gazebo simulation framework was employed again to evaluate the global path in the sideways wind, which is the most critical scenario among the three types of wind environments.…”

Section: Global Path Planning Resultssupporting

confidence: 52%

“…The global path planning algorithm quantifies the energy consumption of a UAV in spatiotemporal wind environment and finds an energy-efficient path. 23 The local path planner assesses the perception quality for a LiDAR-based SLAM algorithm online, enabling robust autonomous flight in GNSS-denied unknown environments. 24 This paper incorporates these global and local planners and elaborates a planning and navigation framework that can drive a UAV to fly along an energy-efficient and SLAM-reliable path.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, this paper addresses an energy and perception aware framework for planning and navigation for UAVs, enabling the UAVs to fly a path with maintaining the energy efficiency and pose estimation accuracy. The proposed framework is elaborated by combining our previous works in Aoki and Ishigami 23 and Takemura and Ishigami 24 for achieving global and local path planning. As in the literatures, 25,26 it is common for local and global planners to solve different problems and to integrate them well.…”

Section: Introductionmentioning

confidence: 99%

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Energy-and-perception-aware planning and navigation framework for unmanned aerial vehicles

Takemura

Aoki

Ishigami

2023

Advances in Mechanical Engineering

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This paper presents an energy and perception aware framework for path planning and navigation of unmanned aerial vehicles (UAVs) in GNSS-denied and spatiotemporal wind environments. The proposed framework mainly consists of the global and local path planning methods that respectively consider the energy consumption of an UAV and perception quality of a light detection and ranging (LiDAR) sensor mounted on the UAV. The energy consumption is estimated based on the aerodynamic model that calculates drag and lift forces on the UAV. The global planner then uses the total energy consumption in the spatiotemporal wind as the cost function to find an energy-efficient path as a set of waypoints. The local path planning navigates the UAV between the waypoints with maintaining the perception quality. The perception quality is quantified based on how well the LiDAR sensor scans feature points around the UAV that highly correlates with the navigation accuracy. Numerical simulation study for each of the global and local path planners validates their usefulness. Further, the overall framework is entirely verified in a long-range flight scenario of the photorealistic environments developed in the Gazebo simulation.

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Section: Global Path Planning Resultssupporting

confidence: 52%

Section: Introductionmentioning

confidence: 99%