USVDDPGpath planningDRLPath planning is crucial in the automatic navigation of USVs (unmanned underwater vehicles), which directly affects the operational efficiency and safety of USVs. In this paper, we propose
Planning an obstacle-free optimal path presents great challenges for mobile robot applications, the deep deterministic policy gradient (DDPG) algorithm offers an effective solution. However, when the original DDPG is applied to robot path planning, there
Through a series of simulation experiments, it can be observed that the optimal path for USVs found by the DDPG-based path planning algorithm is faster and more accurate than that found by the other two methods. The experimental results show that the DDPG algorithm has a significant advantage ...
PID Controller Based on Improved DDPG for Trajectory Tracking Control of USV. J. Mar. Sci. Eng. 2024, 12, 1771. [Google Scholar] [CrossRef] Song, A.; Wang, N.; Li, J.; Ma, B.; Chen, X. Transient flow characteristics and performance of a solid rocket motor with a pintle valve...
PID Controller Based on Improved DDPG for Trajectory Tracking Control of USV. J. Mar. Sci. Eng. 2024, 12, 1771. [Google Scholar] [CrossRef] Song, A.; Wang, N.; Li, J.; Ma, B.; Chen, X. Transient flow characteristics and performance of a solid rocket motor with a pintle valve...
Correspondingly, a vision-based guidance algorithm can be used to obtain the relative position and attitude of the AUV with reference to the DS. Vision-based guidance can also calculate the attitude error of AUV through the visual information, and plan the target point C at the DS position. ...
This paper proposes a path-tracking control method for a single-outboard-motor USV based on a Deep Deterministic Policy Gradient (DDPG) algorithm and model predictive control (MPC) algorithm. Initially, the motion model and outboard motor model of the USV are analyzed. Subsequently, simulation and...
First, we develop an improved APF-RRT* algorithm for motion planning of the mobile robotic arm. It optimizes the process of expanding random trees, and the path is simplified via APF. Second, a Fuzzy-DDPG-PID controller is established for tracking control of the mobile robotic arm. We ...
First, we develop an improved APF-RRT* algorithm for motion planning of the mobile robotic arm. It optimizes the process of expanding random trees, and the path is simplified via APF. Second, a Fuzzy-DDPG-PID controller is established for tracking control of the mobile robotic arm. We ...