Human Robot Collaboration in Industrial Environments

Industry 4.0, also termed smart manufacturing, has revolutionized the industrial world with cutting-edge technologies such as collaborative robots and artificial intelligence etc. Productivity and efficiency are two key factors that determine the success level of manufacturing. Therefore, many manufacturers have become so eager to adopt adaptive, intuitive, collaborative and smart techniques to improve the production lines, including key manufacturing machines and equipment. Therefore, robotic systems are playing an increasingly vital role in many industrial sectors, as they decrease the need for human labour and increase automation level. In addition, material waste can be also reduced since robots provide stability and accuracy during work. In turn, production times are reduced as well. Consequently, smart manufacturing areas need more advanced, flexible, and smart robotic systems to respond to market size changes and customization processes. As a result, currently, great research efforts are made to enrich the interactions between humans and robots in the work environment. This paper presents an overview of Human-Robot Collaboration (HRC) systems being employed in smart manufacturing to exploit the benefits of human experience and the capabilities of robotic systems. The research gaps, challenges and future work directions on HRC are highlighted and analyzed towards smart manufacturing.

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“…HRC system is implemented in many industrial sectors such as the automotive industry and food processing [35].…”

Section: B) Hrc In Smart Manufacturing -Industrial Casesmentioning

confidence: 99%

An Overview of Human-Robot Collaboration in Smart Manufacturing

Othman

Yang

2022

2022 27th International Conference on Automation and Computing (ICAC)

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“…The typical cobot is a stationary arm capable of lifting and manipulating an object weighing a few kilograms. Uncommonly, capacities for large payloads exist: the COMAU ORA can carry 170 kg (Michalos et al, 2022). The larger a payload an arm can carry, however, the greater potential harm to a human operator working close to it.…”

Section: "Collaboration" and Collaborative Robotsmentioning

confidence: 99%

Cobots, “co-operation” and the replacement of human skill

Sorell

2022

Ethics Inf Technol

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Automation does not always replace human labour altogether: there is an intermediate stage of human co-existence with machines, including robots, in a production process. Cobots are robots designed to participate at close quarters with humans in such a process. I shall discuss the possible role of cobots in facilitating the eventual total elimination of human operators from production in which co-bots are initially involved. This issue is complicated by another: cobots are often introduced to workplaces with the message (from managers) that they will not replace human operators but will rather assist human operators and make their jobs more interesting and responsible. If, in the process of learning to assist human operators, robots acquire the skills of human operators, then the promise of avoiding replacement can turn out to be false, and if a human operator loses his job, he has been harmed twice over: once by unemployment and once by deception. I shall suggest that this moral risk attends some cobots more than others.

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“…M OVING a robot in the real world presents several challenges, including adapting the robot's motion to the dynamic nature of the environment. This problem has become very important in recent years with the spread of mobile robotics [1], social robotics [2], and human-robot collaboration (HRC) in industrial settings [3]. Path planners usually plan a path from a start point to a goal point, considering only static obstacles.…”

Section: Introductionmentioning

confidence: 99%

Anytime Informed Multi-Path Replanning Strategy for Complex Environments

et al. 2023

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In many real-world applications (e.g., human-robot collaboration), the environment changes rapidly, and the intended path may become invalid due to moving obstacles. In these situations, the robot should quickly find a new path to reach the goal, possibly without stopping. Planning from scratch or repairing the current graph can be too expensive and time-consuming. This paper proposes a path replanner, MARS, that enables a robot to move in dynamic environments with unpredictable obstacles. The method exploits a set of pre-computed paths to compute a new solution in a few hundred milliseconds when an obstacle obstructs the robot's way. It enhances the search speed using informed sampling and improves the current solution in an anytime fashion to make the robot reactive to environmental changes. In addition, the paper presents a multithread architecture, applicable to several replanning algorithms, to handle the execution of the robot's trajectory with continuous replanning and the collision checking of the traversed path. The paper compares state-of-the-art sampling-based path-replanning algorithms in complex and high-dimensional scenarios, showing that MARS is superior in terms of success rate and quality of solutions found. An open-source ROS-compatible implementation of the algorithm is also provided.

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Human Robot Collaboration in Industrial Environments

Cited by 17 publications

References 43 publications

An Overview of Human-Robot Collaboration in Smart Manufacturing

An Overview of Human-Robot Collaboration in Smart Manufacturing

Cobots, “co-operation” and the replacement of human skill

Anytime Informed Multi-Path Replanning Strategy for Complex Environments

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