A New Approach for Training Cobots from Small Amount of Data in Industry 5.0

摘要

Machine learning is a vital part of today's world. Although the current Machine Learning slogan is “big data is required for a smarter AI”. All Artificial Intelligence learning techniques require the training of algorithms with huge data. Collecting and storing this data takes time and requires increasing computer memory. In Industry 5.0, human-robot collaboration is a challenge for artificial intelligence (AI) and its subdomains. Indeed, integration of its domains is required. Many AI techniques are needed, ranging from visual processing to symbolic reasoning, task planning to mind building theory, reactive control to action recognition and learning. Otherwise, the main two obstacles to this natural workflow interaction are big data memorization and time Learning that grows exponentially with the problem complexity especially. In this article, we propose a new approach for training Cobots from Small Amount of Data in the context of industry 5.0 based on common-sense capability inspired by human learning.