TY - JOUR
T1 - BPMP-Tracker
T2 - A Versatile Aerial Target Tracker Using Bernstein Polynomial Motion Primitives
AU - Lee, Yunwoo
AU - Park, Jungwon
AU - Jeon, Boseong
AU - Jung, Seungwoo
AU - Kim, H. Jin
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - motion and path planning
KW - Reactive and sensor-based planning
KW - visual servoing
UR - https://www.scopus.com/pages/publications/85207000061
U2 - 10.1109/LRA.2024.3475879
DO - 10.1109/LRA.2024.3475879
M3 - Article
AN - SCOPUS:85207000061
SN - 2377-3766
VL - 9
SP - 10938
EP - 10945
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 12
ER -