Downloads provided by UsageCounts
handle: 11380/1156534
Abstract Easy-to-use collaborative robotics solutions, where human workers and robots share their skills, are entering the market, thus becoming the new frontier in industrial robotics. They allow to combine the advantages of robots, which enjoy high levels of accuracy, speed and repeatability, with the flexibility and cognitive skills of human workers. However, to achieve an efficient human–robot collaboration, several challenges need to be tackled. First, a safe interaction must be guaranteed to prevent harming humans having a direct contact with the moving robot. Additionally, to take full advantage of human skills, it is important that intuitive user interfaces are properly designed, so that human operators can easily program and interact with the robot. In this survey paper, an extensive review on human–robot collaboration in industrial environment is provided, with specific focus on issues related to physical and cognitive interaction. The commercially available solutions are also presented and the main industrial applications where collaborative robotic is advantageous are discussed, highlighting how collaborative solutions are intended to improve the efficiency of the system and which the open issue are.
Collaborative robots; Human-robot collaboration; Industrial applications; Intuitive robot programming; Safety; User interfaces; Mechanical Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineering
Collaborative robots; Human-robot collaboration; Industrial applications; Intuitive robot programming; Safety; User interfaces; Mechanical Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineering
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 944 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 0.01% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 0.1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.1% |
| views | 136 | |
| downloads | 430 |

Views provided by UsageCounts
Downloads provided by UsageCounts