A Control System Design and Implementation for Autonomous Quadrotors with Real-Time Re-Planning Capability

Real-time (re-)planning is crucial for autonomous quadrotors to navigate in uncertain environments where obstacles may be detected and trajectory plans must be adjusted on-the-fly to avoid collision. In this paper, we present a control system design for autonomous quadrotors that has real-time re-planning capability, including the hardware pipeline for the hardware–software integration to realize the proposed real-time re-planning algorithm. The framework is based on a modified version of the PX4 Autopilot and a Raspberry Pi 5 companion computer. The planning algorithm utilizes minimum-snap trajectory generation, taking advantage of the differential flatness property of quadrotors, to realize computationally light, real-time re-planning using an onboard computer. We first verify the control system and the planning algorithm through simulation experiments, followed by implementing and demonstrating the system on hardware using a quadcopter.

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Publication Details

Journal
Robotics
Published
2024-09-09
DOI
https://doi.org/10.3390/robotics13090136
Citations
7
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
1.74
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article

A Control System Design and Implementation for Autonomous Quadrotors with Real-Time Re-Planning Capability

Ehsan Taheri, Yevhenii Kovryzhenko, Nan Li
7 citations
Robotics
Robotic Path Planning Algorithms
1.74
article

A Control System Design and Implementation for Autonomous Quadrotors with Real-Time Re-Planning Capability

Ehsan Taheri, Yevhenii Kovryzhenko, Nan Li
article en
7 citations

Abstract

Real-time (re-)planning is crucial for autonomous quadrotors to navigate in uncertain environments where obstacles may be detected and trajectory plans must be adjusted on-the-fly to avoid collision. In this paper, we present a control system design for autonomous quadrotors that has real-time re-planning capability, including the hardware pipeline for the hardware–software integration to realize the proposed real-time re-planning algorithm. The framework is based on a modified version of the PX4 Autopilot and a Raspberry Pi 5 companion computer. The planning algorithm utilizes minimum-snap trajectory generation, taking advantage of the differential flatness property of quadrotors, to realize computationally light, real-time re-planning using an onboard computer. We first verify the control system and the planning algorithm through simulation experiments, followed by implementing and demonstrating the system on hardware using a quadcopter.

RoboticsVol. 13(9)
Tongji University (CN), Auburn University (US)
Openalex Percentile: Top 14%
Robotic Path Planning Algorithms
1.74
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