QP Chaser: Polynomial Trajectory Generation for Autonomous Aerial Tracking

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Lee, Yunwoo, Park, Jungwon, Jung, Seungwoo, Jeon, Boseong, Oh, Dahyun, Kim, H. Jin
Natura: Preprint
Pubblicazione: 2023
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866908641363230720
author Lee, Yunwoo
Park, Jungwon
Jung, Seungwoo
Jeon, Boseong
Oh, Dahyun
Kim, H. Jin
author_facet Lee, Yunwoo
Park, Jungwon
Jung, Seungwoo
Jeon, Boseong
Oh, Dahyun
Kim, H. Jin
contents Maintaining the visibility of the target is one of the major objectives of aerial tracking missions. This paper proposes a target-visible trajectory planning pipeline using quadratic programming. Our approach can handle various tracking settings, including single and dual target following and both static and dynamic environments, unlike other works that focus on a single specific setup. In contrast to other studies that fully trust the predicted trajectory of the target and consider only the visibility of the center of the target, our pipeline considers error in target path prediction and the entire body of the target to maintain the target visibility robustly. First, a prediction module uses a sample-check strategy to quickly calculate the reachable areas of moving objects, which represent the areas their bodies can reach, considering obstacles. Subsequently, the planning module formulates a single QP problem, considering path homotopy, to generate a tracking trajectory that maximizes the visibility of the target's reachable area among obstacles. The performance of the planner is validated in multiple scenarios, through high-fidelity simulations and real-world experiments.
format Preprint
id arxiv_https___arxiv_org_abs_2302_14273
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle QP Chaser: Polynomial Trajectory Generation for Autonomous Aerial Tracking
Lee, Yunwoo
Park, Jungwon
Jung, Seungwoo
Jeon, Boseong
Oh, Dahyun
Kim, H. Jin
Robotics
Systems and Control
Maintaining the visibility of the target is one of the major objectives of aerial tracking missions. This paper proposes a target-visible trajectory planning pipeline using quadratic programming. Our approach can handle various tracking settings, including single and dual target following and both static and dynamic environments, unlike other works that focus on a single specific setup. In contrast to other studies that fully trust the predicted trajectory of the target and consider only the visibility of the center of the target, our pipeline considers error in target path prediction and the entire body of the target to maintain the target visibility robustly. First, a prediction module uses a sample-check strategy to quickly calculate the reachable areas of moving objects, which represent the areas their bodies can reach, considering obstacles. Subsequently, the planning module formulates a single QP problem, considering path homotopy, to generate a tracking trajectory that maximizes the visibility of the target's reachable area among obstacles. The performance of the planner is validated in multiple scenarios, through high-fidelity simulations and real-world experiments.
title QP Chaser: Polynomial Trajectory Generation for Autonomous Aerial Tracking
topic Robotics
Systems and Control
url https://arxiv.org/abs/2302.14273