Real-time Trajectory Planning and Tracking Control of Bionic Underwater Robot in Dynamic Environment
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Top Cited Papers
Open Access
- 1 January 2024
- journal article
- research article
- Published by American Association for the Advancement of Science (AAAS) in Cyborg and Bionic Systems
- Vol. 5, 0112
Abstract
In this article, we study the trajectory planning and tracking control of a bionic underwater robot under multiple dynamic obstacles. We first introduce the design of the bionic leopard cabinet underwater robot developed in our lab. Then, we model the trajectory planning problem of the bionic underwater robot by combining its dynamics and physical constraints. Furthermore, we conduct global trajectory planning for bionic underwater robots based on the temporal-spatial Bezier curves. In addition, based on the improved proximal policy optimization, local dynamic obstacle avoidance trajectory replanning is carried out. In addition, we design the fuzzy proportional-integral-derivative controller for tracking control of the planned trajectory. Finally, the effectiveness of the real-time trajectory planning and tracking control method is verified by comparative simulation in dynamic environment and semiphysical simulation of UWSim. Among them, the real-time trajectory planning method has advantages in trajectory length, trajectory smoothness, and planning time. The error of trajectory tracking control method is controlled around 0.2 m.Keywords
Funding Information
- The National Natural Science Foundation of China (62276253, 62203435)
- the Beijing Nova Program (Z211100002121152, 20230484457)
This publication has 34 references indexed in Scilit:
- A Novel Ultrasound Robot With Force/Torque Measurement and Control for Safe and Efficient ScanningIEEE Transactions on Instrumentation and Measurement, 2023
- Deep-Learning-Assisted Underwater 3D Tactile TensegrityResearch, 2023
- Deep reinforcement learning for adaptive path planning and control of an autonomous underwater vehicleApplied Ocean Research, 2022
- Hydrodynamic Modeling and Parameter Identification of a Bionic Underwater Vehicle: RobDactCyborg and Bionic Systems, 2022
- Multiple Bio-Inspired Father–Son Underwater Robot for Underwater Target Object Acquisition and IdentificationMicromachines, 2021
- Data-Driven Performance-Prescribed Reinforcement Learning Control of an Unmanned Surface VehicleIEEE Transactions on Neural Networks and Learning Systems, 2021
- Reinforcement Learning-Based Optimal Tracking Control of an Unknown Unmanned Surface VehicleIEEE Transactions on Neural Networks and Learning Systems, 2020
- Reinforcement Learning-Based Multi-AUV Adaptive Trajectory Planning for Under-Ice Field EstimationSensors, 2018
- Research on fuzzy control of path tracking for underwater vehicle based on genetic algorithm optimizationOcean Engineering, 2018
- PID type fuzzy controller and parameters adaptive methodFuzzy Sets and Systems, 1996