Trajectory Planning Towards Water-Air Trans-Media Motion for Robotic Dolphin

Water-air trans-media navigators have multi-media motion modes, breaking through the limitation that traditional robots can only operate in a single medium. Autonomous navigation is an indispensable component of the process of transmedia motion. Most of the current work has only completed the development and testing of prototypes, and the problem of task-oriented motion planning and control needs to be solved. In this paper, a safe and efficient hierarchical approach is proposed. First, a novel rapidly exploring random tree-based algorithm is proposed to search for a suitable path. Then, by fixing bound waypoints, the time-optimization trajectory is planned. Finally, the trajectory tracker is designed based on nonlinear model predictive control (NMPC). Simulation experiments numerically validate the proposed method, offering some new insights for further trans-media motions.

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Publication Details

Published
2024-11-01
DOI
https://doi.org/10.1109/cac63892.2024.10865408
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Trajectory Planning Towards Water-Air Trans-Media Motion for Robotic Dolphin

Junzhi Yu, Di Chen, Pengfei Zhang, Yan Xiong
Underwater Vehicles and Communication Systems
article

Trajectory Planning Towards Water-Air Trans-Media Motion for Robotic Dolphin

Junzhi Yu, Di Chen, Pengfei Zhang, Yan Xiong
article en

Abstract

Water-air trans-media navigators have multi-media motion modes, breaking through the limitation that traditional robots can only operate in a single medium. Autonomous navigation is an indispensable component of the process of transmedia motion. Most of the current work has only completed the development and testing of prototypes, and the problem of task-oriented motion planning and control needs to be solved. In this paper, a safe and efficient hierarchical approach is proposed. First, a novel rapidly exploring random tree-based algorithm is proposed to search for a suitable path. Then, by fixing bound waypoints, the time-optimization trajectory is planned. Finally, the trajectory tracker is designed based on nonlinear model predictive control (NMPC). Simulation experiments numerically validate the proposed method, offering some new insights for further trans-media motions.

Peking University (CN), China General Nuclear Power Corporation (China) (CN), State Key Laboratory of Turbulence and Complex Systems, University of Science and Technology Beijing (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 64%
Underwater Vehicles and Communication Systems
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