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Toward the Intelligent, Safe Exploration of a Biomimetic Underwater Robot: Modeling, Planning, and Control
Yu Wang1, Jian Wang2,3, Lianyi Yu2,3
1Department of Automation, Tsinghua University, Beijing 100084, China.
Biomimetics (Basel, Switzerland)
|March 27, 2024
Summary
This study presents an intelligent framework for biomimetic robots to navigate underwater environments safely. The system uses deep reinforcement learning and a backstepping method for obstacle avoidance and motion planning, enabling effective ocean exploration.
Area of Science:
- Robotics
- Oceanography
- Artificial Intelligence
Background:
- Underwater exploration is challenging due to complex environments like coral reefs and obstacles.
- Existing methods lack intelligent navigation and obstacle avoidance capabilities for robotic systems.
Purpose of the Study:
- To develop an intelligent underwater exploration framework for biomimetic robots.
- To enable safe and efficient autonomous navigation in complex marine environments.
Main Methods:
- An obstacle detection and collision model using onboard sensors was established.
- Deep reinforcement learning was employed for planar motion planning.
- A backstepping method with a sigmoid function was used for yaw control.
Main Results:
- The biomimetic robot successfully achieved intelligent motion planning.
- The system demonstrated effective yaw control with obstacle avoidance.
- Simulations verified the framework's effectiveness in complex underwater scenarios.
Conclusions:
- The proposed framework offers a valuable solution for autonomous underwater operations.
- The biomimetic robot can navigate and perform tasks in challenging marine environments.
- The integration of AI and control methods enhances underwater exploration capabilities.
