Robust Precision Landing of a Quadrotor with Online Temporal Scaling Adaptation of Dynamic Movement Primitives

In this work, we address the challenges of robust precision landing maneuvers for a quadrotor on both stationary and moving ground targets in the presence of disturbances that can cause the quadrotor to deviate from its desired trajectory, leading to maneuver failure. To overcome this, we propose a novel online adaptive trajectory planning approach based on the online temporal scaling adaptation of dynamic movement primitives (DMPs). This adaptation enables the desired trajectory to be dynamically adjusted in response to tracking errors and the goal’s state. Consequently, our proposed approach enhances accuracy, precision, and safety during landing maneuvers. The effectiveness of the approach is evaluated through comprehensive experiments conducted in both physical simulations and real-world environments, covering various disturbance scenarios.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10801311
Citations
1
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.33
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article

Robust Precision Landing of a Quadrotor with Online Temporal Scaling Adaptation of Dynamic Movement Primitives

Poramate Manoonpong, Prakarn Jaroonsorn, Pakpoom Kriengkomol, Kongkiat Rothomphiwat
1 citations
Robot Manipulation and Learning
0.33
article

Robust Precision Landing of a Quadrotor with Online Temporal Scaling Adaptation of Dynamic Movement Primitives

Poramate Manoonpong, Prakarn Jaroonsorn, Pakpoom Kriengkomol, Kongkiat Rothomphiwat
article en
1 citations

Abstract

In this work, we address the challenges of robust precision landing maneuvers for a quadrotor on both stationary and moving ground targets in the presence of disturbances that can cause the quadrotor to deviate from its desired trajectory, leading to maneuver failure. To overcome this, we propose a novel online adaptive trajectory planning approach based on the online temporal scaling adaptation of dynamic movement primitives (DMPs). This adaptation enables the desired trajectory to be dynamically adjusted in response to tracking errors and the goal’s state. Consequently, our proposed approach enhances accuracy, precision, and safety during landing maneuvers. The effectiveness of the approach is evaluated through comprehensive experiments conducted in both physical simulations and real-world environments, covering various disturbance scenarios.

PTT Public Company Limited (Thailand) (TH), Vidyasirimedhi Institute of Science and Technology (TH)
Openalex Percentile: Top 38%
Robot Manipulation and Learning
0.33
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