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Development of an Orchard Inspection Robot: A ROS-Based LiDAR-SLAM System with Hybrid A*-DWA Navigation.

Jiwei Qu¹, Yanqiu Gu¹, Zhinuo Qiu¹

¹School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China.

Sensors (Basel, Switzerland)

|November 13, 2025

Summary

This summary is machine-generated.

This study enhances autonomous navigation for orchard inspection robots using Simultaneous Localization and Mapping (SLAM) with LiDAR. The developed system offers efficient path planning and accurate obstacle avoidance for improved robotic operations.

Keywords:

SLAM autonomous navigation information perception intelligent equipment mobile robot obstacle avoidance

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Area of Science:

Robotics and Automation
Artificial Intelligence
Computer Vision

Background:

Autonomous navigation in unstructured environments like orchards presents significant challenges for inspection robots.
Existing systems often struggle with precise localization and efficient path planning, limiting operational capabilities.

Purpose of the Study:

To investigate and evaluate a Simultaneous Localization and Mapping (SLAM) navigation system for orchard inspection robots.
To enhance autonomous navigation capabilities through sensor fusion and advanced path planning algorithms.

Main Methods:

Development of a multi-sensor mobile robot integrating Light Detection and Ranging (LiDAR) and Inertial Measurement Units (IMUs).
Establishment of the robot's kinematic model and coordinate transformations using the Unified Robotics Description Format (URDF) within the Robot Operating System (ROS).
Implementation of an improved A* algorithm combined with the Dynamic Window Approach (DWA) for global and local path planning.

Main Results:

The integrated SLAM system demonstrated superior search efficiency and path smoothness compared to classical algorithms in simulations.
Navigation accuracy tests showed an average lateral deviation of 0.163 m and longitudinal deviation of 0.282 m at waypoints.
Effective obstacle avoidance was achieved, with optimal performance observed at an expansion radius of 0.4 m.

Conclusions:

The proposed combined path planning method provides efficient and stable autonomous navigation for orchard inspection robots.
The system's performance in localization, path planning, and obstacle avoidance offers a valuable reference for future robotic applications in agriculture.