Forklift localization and tracking in warehouse settings

In warehouses, it’s important to know where forklifts are for safety and efficiency. Visual SLAM is a promising approach for forklift localization and navigation for indoor applications, but current methods have problems like being slow, not understanding what they see, and being affected by changes in light. This project aims to solve these problems and make a strong system to find and track forklifts in warehouses. It will focus on finding and matching features, localization, understanding the environment, and keeping the map updated. The successful completion of this project will make great contributions to intelligent warehouse management. It introduces capabilities such as real-time inventory tracking, optimized storage layouts for efficiency, dynamic resource allocation, and streamlined order fulfillment. These outcomes have the capacity to positively impact Canada’s economy, trade relations, and technological standing.

Faculty Supervisor:

Guanghui Wang

Student:

Partner:

Antek Logistics

Discipline:

Computer science

Sector:

Transportation and warehousing

University:

Toronto Metropolitan University

Program: