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

  • Yunwoo Lee
  • , Jungwon Park
  • , Boseong Jeon
  • , Seungwoo Jung
  • , H. Jin Kim

Research output: Contribution to journalArticlepeer-review

1 Scopus 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 sample-check-select 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.

Original languageEnglish
Pages (from-to)10938-10945
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume9
Issue number12
DOIs
StatePublished - 2024

Keywords

  • motion and path planning
  • Reactive and sensor-based planning
  • visual servoing

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