Sequential Convex Programming for Time-optimal Quadrotor Waypoint Flight

Agile flight is significant for target tracking, search and rescue, and delivery applications. To achieve agile flight, we can exploit the actuator’s potential by utilizing the full dynamics of the quadrotor. However, the 6-degrees-of-freedom dynamics render the optimization problem non-convex, and thus computationally intractable. To tackle this issue, we convert the original non-convex optimal control problem (OCP) into a convex subproblem and use the sequential convex programming (SCP) algorithm to iteratively solve the subproblems. Moreover, the state-triggered constraints are proposed to simultaneously optimize the time allocation of the waypoint and the trajectory itself. The numerical and physical experiment results<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> show that the SCP algorithm can significantly reduce the computing time while ensuring a satisfactory solution.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802749
Citations
1
Primary Topic
Spacecraft Dynamics and Control
Type
article
Field-Weighted Citation Impact
1.30

Funders

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article

Sequential Convex Programming for Time-optimal Quadrotor Waypoint Flight

Hailong Huang, Guanzhong Zhou, Zhipeng Shen
1 citations
Spacecraft Dynamics and Control
1.30
article

Sequential Convex Programming for Time-optimal Quadrotor Waypoint Flight

Hailong Huang, Guanzhong Zhou, Zhipeng Shen
article en
1 citations

Abstract

Agile flight is significant for target tracking, search and rescue, and delivery applications. To achieve agile flight, we can exploit the actuator’s potential by utilizing the full dynamics of the quadrotor. However, the 6-degrees-of-freedom dynamics render the optimization problem non-convex, and thus computationally intractable. To tackle this issue, we convert the original non-convex optimal control problem (OCP) into a convex subproblem and use the sequential convex programming (SCP) algorithm to iteratively solve the subproblems. Moreover, the state-triggered constraints are proposed to simultaneously optimize the time allocation of the waypoint and the trajectory itself. The numerical and physical experiment results<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> show that the SCP algorithm can significantly reduce the computing time while ensuring a satisfactory solution.

Hong Kong Polytechnic University (HK)
Hong Kong Polytechnic University
Openalex Percentile: Top 11%
Spacecraft Dynamics and Control
1.30
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