Smooth 3D Dubins Curves Based Mobile Data Gathering in Sparse Underwater Sensor Networks.

Area of Science:

• Robotics and Autonomous Systems
• Underwater Sensor Networks
• Data Acquisition

Background:

• Underwater sensor networks (USNs) face challenges with full connectivity, necessitating mobile data gathering.
• Autonomous underwater vehicles (AUVs) are employed to address energy imbalance and data collection in sparse 3D USNs.
• AUVs mitigate energy-intensive multi-hop transmissions by collecting data from nodes.

Purpose of the Study:

• To develop a mobile data gathering mechanism for 3D USNs using AUVs.
• To overcome kinematic nonholonomic constraints of AUVs during data collection.
• To optimize path planning and movement control strategies for AUVs in USNs.

Main Methods:

• Proposed a smooth 3D Dubins curves based mobile data gathering mechanism.
• Utilized continuous Bezier curves for Z-axis interpolation of 2D Dubins curves.
• Employed AUVs for efficient data collection and transmission between sensor nodes.

Main Results:

• Achieved significantly smoother data collection paths for AUVs.
• Demonstrated reduced energy consumption in mobile data gathering operations.
• Verified the efficiency of the proposed method through extensive simulations.

Conclusions:

• The proposed smooth 3D Dubins curves method is highly suitable for mobile data collection in 3D underwater sensor networks.
• This approach enhances overall performance in terms of path smoothness and energy efficiency.
• Optimized AUV path planning is crucial for effective data acquisition in USNs.