Intention-Aware Planner for Robust and Safe Aerial Tracking

Fuente: arXiv
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Autores principales: Ren, Qiuyu, Yu, Huan, Dai, Jiajun, Zheng, Zhi, Meng, Jun, Xu, Li, Xu, Chao, Gao, Fei, Cao, Yanjun
Formato: Preprint
Publicado: 2023
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author Ren, Qiuyu
Yu, Huan
Dai, Jiajun
Zheng, Zhi
Meng, Jun
Xu, Li
Xu, Chao
Gao, Fei
Cao, Yanjun
author_facet Ren, Qiuyu
Yu, Huan
Dai, Jiajun
Zheng, Zhi
Meng, Jun
Xu, Li
Xu, Chao
Gao, Fei
Cao, Yanjun
contents Autonomous target tracking with quadrotors has wide applications in many scenarios, such as cinematographic follow-up shooting or suspect chasing. Target motion prediction is necessary when designing the tracking planner. However, the widely used constant velocity or constant rotation assumption can not fully capture the dynamics of the target. The tracker may fail when the target happens to move aggressively, such as sudden turn or deceleration. In this paper, we propose an intention-aware planner by additionally considering the intention of the target to enhance safety and robustness in aerial tracking applications. Firstly, a designated intention prediction method is proposed, which combines a user-defined potential assessment function and a state observation function. A reachable region is generated to specifically evaluate the turning intentions. Then we design an intention-driven hybrid A* method to predict the future possible positions for the target. Finally, an intention-aware optimization approach is designed to generate a spatial-temporal optimal trajectory, allowing the tracker to perceive unexpected situations from the target. Benchmark comparisons and real-world experiments are conducted to validate the performance of our method.
format Preprint
id arxiv_https___arxiv_org_abs_2309_08854
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Intention-Aware Planner for Robust and Safe Aerial Tracking
Ren, Qiuyu
Yu, Huan
Dai, Jiajun
Zheng, Zhi
Meng, Jun
Xu, Li
Xu, Chao
Gao, Fei
Cao, Yanjun
Robotics
Autonomous target tracking with quadrotors has wide applications in many scenarios, such as cinematographic follow-up shooting or suspect chasing. Target motion prediction is necessary when designing the tracking planner. However, the widely used constant velocity or constant rotation assumption can not fully capture the dynamics of the target. The tracker may fail when the target happens to move aggressively, such as sudden turn or deceleration. In this paper, we propose an intention-aware planner by additionally considering the intention of the target to enhance safety and robustness in aerial tracking applications. Firstly, a designated intention prediction method is proposed, which combines a user-defined potential assessment function and a state observation function. A reachable region is generated to specifically evaluate the turning intentions. Then we design an intention-driven hybrid A* method to predict the future possible positions for the target. Finally, an intention-aware optimization approach is designed to generate a spatial-temporal optimal trajectory, allowing the tracker to perceive unexpected situations from the target. Benchmark comparisons and real-world experiments are conducted to validate the performance of our method.
title Intention-Aware Planner for Robust and Safe Aerial Tracking
topic Robotics
url https://arxiv.org/abs/2309.08854