ROFeb 24, 2022

KinoJGM: A framework for efficient and accurate quadrotor trajectory generation and tracking in dynamic environments

arXiv:2202.12419v412 citations
AI Analysis

This addresses the challenge of safe and efficient real-time navigation for quadrotors in dynamic, unmapped areas, representing a domain-specific incremental advancement.

The paper tackles the problem of autonomous quadrotor navigation in unknown environments with aerodynamic disturbances by proposing a framework that improves trajectory generation efficiency by up to 75% compared to state-of-the-art methods and enhances tracking accuracy.

Unmapped areas and aerodynamic disturbances render autonomous navigation with quadrotors extremely challenging. To fly safely and efficiently, trajectory planners and trackers must be able to navigate unknown environments with unpredictable aerodynamic effects in real-time. When encountering aerodynamic effects such as strong winds, most current approaches to quadrotor trajectory planning and tracking will not attempt to deviate from a determined plan, even if it is risky, in the hope that any aerodynamic disturbances can be resisted by a robust controller. This paper presents a novel systematic trajectory planning and tracking framework for autonomous quadrotors. We propose a Kinodynamic Jump Space Search (Kino-JSS) to generate a safe and efficient route in unknown environments with aerodynamic disturbances. A real-time Gaussian Process is employed to model the effects of aerodynamic disturbances, which we then integrate with a Model Predictive Controller to achieve efficient and accurate trajectory optimization and tracking. We demonstrate our system to improve the efficiency of trajectory generation in unknown environments by up to 75\% in the cases tested, compared with recent state-of-the-art. We also demonstrate that our system improves the accuracy of tracking in selected environments with unpredictable aerodynamic effects.

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