Indoor Positioning, Artificial Intelligence and Digital Twins for Enhanced Robotics Safety
Pitkäaho, Tomi; Kaarlela, Tero; Pieskä, Sakari; Sarlin, Sami (2021)
Pitkäaho, Tomi
Kaarlela, Tero
Pieskä, Sakari
Sarlin, Sami
Elsevier Science Publishers BV
2021
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2022012610326
https://urn.fi/URN:NBN:fi-fe2022012610326
Tiivistelmä
Flexible robotics safety solutions allowing the implementation of fenceless robot
cells are becoming a reality nowadays. Safety approved sensors such as light curtains, safety
scanners, and safety cameras have been deployed already successfully in various industrial
robotic solutions. Still, as these safety systems are installed in fixed locations, monitoring
predefined regions, the systems can be rigid and inflexible. This paper introduces a novel hybrid
safety solution. The solution comprises safety-approved sensors, additional sensors, and artificial
intelligence analysis. The system increases flexibility, especially in cases where collaborating
humans and robots need monitoring in larger areas. Typically, in such environments, work
objects are large and heavy, introducing additional challenges. In addition, the proposed system
includes a digital twin implementation that allows a connection between the real and virtual
worlds. Already virtual models and robot simulation have been used for designing safe robot
applications. However, the efficient use of digital twins in safety planning and safety monitoring
is still uncommon.
cells are becoming a reality nowadays. Safety approved sensors such as light curtains, safety
scanners, and safety cameras have been deployed already successfully in various industrial
robotic solutions. Still, as these safety systems are installed in fixed locations, monitoring
predefined regions, the systems can be rigid and inflexible. This paper introduces a novel hybrid
safety solution. The solution comprises safety-approved sensors, additional sensors, and artificial
intelligence analysis. The system increases flexibility, especially in cases where collaborating
humans and robots need monitoring in larger areas. Typically, in such environments, work
objects are large and heavy, introducing additional challenges. In addition, the proposed system
includes a digital twin implementation that allows a connection between the real and virtual
worlds. Already virtual models and robot simulation have been used for designing safe robot
applications. However, the efficient use of digital twins in safety planning and safety monitoring
is still uncommon.