Wheeled Robots Path Planing and Tracking System Based on Monocular Visual SLAM

TL;DR

This paper presents a monocular visual SLAM-based system for warehouse robots that enables efficient environment perception, obstacle mapping, and path planning without modifying existing warehouse infrastructure.

Contribution

It introduces a novel integrated system combining visual odometry, 3D obstacle mapping, and A* path planning for warehouse robots using monocular cameras.

Findings

Effective obstacle detection and mapping in warehouse environments.

Path planning accuracy verified through simulations and experiments.

System enables fast, reliable navigation without infrastructure changes.

Abstract

Warehouse logistics robots will work in different warehouse environments. In order to enable robots to perceive environment and plan path faster without modifying existing warehouses, we uses monocular camera to achieve an efficient robot integrated system. Mapping and path planning the two main tasks presented in this paper. The direct method visual odometry is applied to localize, and the 3D position of major obstacles in the environment is calculated. We describe the terrain with occupied grid map, the 3D points are projected onto the robot motion plane, thus accessibility of each grid is determined. Based on the terrain information, the optimized A* algorithm is used for path planning. Finally, according to localization and planning, we control the robot to track path. We also develop a path-tracking robot prototype. Simulation and experimental results verify the effectiveness and reliability of the proposed method.