EANS: Reducing Energy Consumption for UAV with an Environmental Adaptive Navigation Strategy

TL;DR

This paper presents an adaptive navigation strategy for UAVs that dynamically adjusts to environmental conditions, significantly reducing energy consumption and extending mission time compared to static methods.

Contribution

It introduces a novel method for real-time adjustment of UAV navigation strategies based on environmental and dynamic analysis, improving energy efficiency.

Findings

3.2X improvement in mission time in HIL simulation

2.4X reduction in energy consumption in real-world experiments

Effective adaptation to environmental changes enhances UAV efficiency

Abstract

Unmanned Aerial Vehicles (UAVS) are limited by the onboard energy. Refinement of the navigation strategy directly affects both the flight velocity and the trajectory based on the adjustment of key parameters in the UAVS pipeline, thus reducing energy consumption. However, existing techniques tend to adopt static and conservative strategies in dynamic scenarios, leading to inefficient energy reduction. Dynamically adjusting the navigation strategy requires overcoming the challenges including the task pipeline interdependencies, the environmental-strategy correlations, and the selecting parameters. To solve the aforementioned problems, this paper proposes a method to dynamically adjust the navigation strategy of the UAVS by analyzing its dynamic characteristics and the temporal characteristics of the autonomous navigation pipeline, thereby reducing UAVS energy consumption in response to environmental changes. We compare our method with the baseline through hardware-in-the-loop (HIL) simulation and real-world experiments, showing our method 3.2X and 2.6X improvements in mission time, 2.4X and 1.6X improvements in energy, respectively.