Reprint

Human-Robot Collaborations in Industrial Automation

Edited by
September 2022
228 pages
  • ISBN978-3-0365-5213-2 (Hardback)
  • ISBN978-3-0365-5214-9 (PDF)

This is a Reprint of the Special Issue Human-Robot Collaborations in Industrial Automation that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary

Technology is changing the manufacturing world. For example, sensors are being used to track inventories from the manufacturing floor up to a retail shelf or a customer’s door. These types of interconnected systems have been called the fourth industrial revolution, also known as Industry 4.0, and are projected to lower manufacturing costs. As industry moves toward these integrated technologies and lower costs, engineers will need to connect these systems via the Internet of Things (IoT). These engineers will also need to design how these connected systems interact with humans. The focus of this Special Issue is the smart sensors used in these human–robot collaborations.

Format
  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
Keywords
physical human-robot interaction; game theory; adaptive optimal control; robot control; tandem force sensor; traction force sensor; human–robot interaction; contact task; imitation learning; safe physical human–robot collaboration; collision detection; human action recognition; artificial intelligence; industrial automation; reinforcement learning; social robotics; human-robot interaction; reward design; physical embodiment; human robot collaboration; human robot interaction; path planning; bidirectional awareness; haptic feedback device; human machine interface; collision identification; collaborative robot; deep learning; uncertainty estimation; knowledge distillation; human–robot collaboration; speed and separation monitoring; human–machine differentiation; thermal cameras; protective separation distance; human–robot interaction; human–robot collaboration; collaborative robots; motion planning; robot control; human motion prediction; human-following robots; teleoperation; high-speed image processing; machine learning; finger position recognition; grasp type estimation; human-robot collaboration; human-centered robotics; task planning; n/a