An autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation

Area of Science:

• Agricultural Robotics
• Forestry Technology
• Autonomous Systems

Background:

• Manual rubber-tapping faces challenges with efficiency and labor.
• Autonomous navigation in complex forest environments is difficult for robots.

Purpose of the Study:

• To design an autonomous navigation system for rubber tapping robots in forest environments.
• To improve the decision-making and path planning capabilities of these robots.

Main Methods:

• Developed a trajectory prediction-based decision mechanism.
• Implemented modules for target point acquisition (OCTP), next coordinate selection (SNC), coordinate generation (GAC), and path optimization (OPP).

Main Results:

• On-site experiments showed favorable positioning accuracy for subsequent operations.
• The planned path rationality reached 92.14%, confirming the system's effectiveness.

Conclusions:

• The developed autonomous navigation system effectively addresses multi-objective navigation challenges in rubber forests.
• The trajectory prediction-based mechanism enables robots to autonomously select targets and optimize paths for efficient rubber tapping.