BPMP-Tracker: A Versatile Aerial Target Tracker Using Bernstein Polynomial Motion Primitives

This letter presents a versatile trajectory planning pipeline for aerial tracking. The proposed tracker is capable of handling various chasing settings such as complex unstructured environments, crowded dynamic obstacles and multiple-target following. Among the entire pipeline, we focus on developing a predictor for future target motion and a chasing trajectory planner. For rapid computation, we employ the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sample-check-select</i> strategy: modules sample a set of candidate movements, check multiple constraints, and then select the best trajectory. Also, we leverage the properties of Bernstein polynomials for quick calculations. The prediction module predicts the trajectories of the targets, which do not overlap with static and dynamic obstacles. Then the trajectory planner outputs a trajectory, ensuring various conditions such as occlusion and collision avoidance, the visibility of all targets within a camera image and dynamical limits. We fully test the proposed tracker in simulations and hardware experiments under challenging scenarios, including dual-target following, environments with dozens of dynamic obstacles and complex indoor and outdoor spaces.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2024-10-11
DOI
https://doi.org/10.1109/lra.2024.3475879
Citations
1
Primary Topic
Target Tracking and Data Fusion in Sensor Networks
Type
article
Field-Weighted Citation Impact
0.35
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article

BPMP-Tracker: A Versatile Aerial Target Tracker Using Bernstein Polynomial Motion Primitives

Boseong Felipe Jeon, Jungwon Park, Yun-Woo Lee, H. Jin Kim et al.
1 citations
IEEE Robotics and Automation Letters
Target Tracking and Data Fusion in Sensor Networks
0.35
article

BPMP-Tracker: A Versatile Aerial Target Tracker Using Bernstein Polynomial Motion Primitives

Boseong Felipe Jeon, Jungwon Park, Yun-Woo Lee, H. Jin Kim, Seung-Woo Jung
article en
1 citations

Abstract

This letter presents a versatile trajectory planning pipeline for aerial tracking. The proposed tracker is capable of handling various chasing settings such as complex unstructured environments, crowded dynamic obstacles and multiple-target following. Among the entire pipeline, we focus on developing a predictor for future target motion and a chasing trajectory planner. For rapid computation, we employ the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sample-check-select</i> strategy: modules sample a set of candidate movements, check multiple constraints, and then select the best trajectory. Also, we leverage the properties of Bernstein polynomials for quick calculations. The prediction module predicts the trajectories of the targets, which do not overlap with static and dynamic obstacles. Then the trajectory planner outputs a trajectory, ensuring various conditions such as occlusion and collision avoidance, the visibility of all targets within a camera image and dynamical limits. We fully test the proposed tracker in simulations and hardware experiments under challenging scenarios, including dual-target following, environments with dozens of dynamic obstacles and complex indoor and outdoor spaces.

IEEE Robotics and Automation LettersVol. 9(12)
Seoul National University of Science and Technology (KR), Seoul National University (KR), Samsung (South Korea) (KR)
Openalex Percentile: Top 33%
Target Tracking and Data Fusion in Sensor Networks
0.35
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BPMP-Tracker: A Versatile Aerial Target Tracker Using Bernstein Polynomial Motion Primitives — Boseong Felipe Jeon, Jungwon Park, et al. · IEEE Robotics and Automation Letters (2024) | TGRS Research Map | TGRS