Open AccessDeep Learning-based mobile robot for warehouse keeping
Author(s) -
Akash Awasthi,
A. Madhu Vamsi,
P. Deeplakshmi
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a1108.1291s419
Subject(s) - warehouse , automation , computer science , obstacle , robot , supply chain , work (physics) , container (type theory) , business , artificial intelligence , engineering , marketing , geography , mechanical engineering , archaeology
As the warehouse plays a crucial role in the supply chain between the manufacturers and end-user or consumers, it is more important to adopt automation in large warehouses and industries. The large e-commerce companies like FLIPKART, AMAZON, SNAPDEAL etc. ship millions of goods and products from one place to another whose distance is in hundreds and even thousands of kilometres. These companies’ warehouses sometimes are as big as nine football pitches or grounds which employ thousands of people for their inventory management. In this technically growing world, we need to reduce the manually done works by efficiently using the automation technology. This paper presents a modified design of Autonomous Inventory Management for Warehouses using automated mobile robots. This proposed work mainly focuses on robotic operations in logistics and warehouses, especially on obstacle avoidance and detection of the destination where it should halt (ie., location of desired object). It will adopt the surroundings by itself by using Machine Learning techniques. Once it reaches the destination, objects will be placed in tote by person and now it will reach preferred location in warehouse.