Benchmark of visual and 3D lidar SLAM systems in simulation environment for vineyards

TL;DR

This paper compares various SLAM systems in a custom vineyard simulation environment, highlighting RTAB-MAP's promising performance amidst challenges like visual changes and uneven terrain.

Contribution

It introduces a vineyard-specific simulation environment and evaluates multiple SLAM systems, providing insights into their performance in challenging agricultural settings.

Findings

RTAB-MAP performs well in vineyard environments

Simulation environment aids SLAM system evaluation in agriculture

Challenges include visual changes and terrain unevenness

Abstract

In this work, we present a comparative analysis of the trajectories estimated from various Simultaneous Localization and Mapping (SLAM) systems in a simulation environment for vineyards. Vineyard environment is challenging for SLAM methods, due to visual appearance changes over time, uneven terrain, and repeated visual patterns. For this reason, we created a simulation environment specifically for vineyards to help studying SLAM systems in such a challenging environment. We evaluated the following SLAM systems: LIO-SAM, StaticMapping, ORB-SLAM2, and RTAB-MAP in four different scenarios. The mobile robot used in this study equipped with 2D and 3D lidars, IMU, and RGB-D camera (Kinect v2). The results show good and encouraging performance of RTAB-MAP in such an environment.