Object Recognition for Safety Applications using Ultrasonic Holography

  • Entering the work envelope of an industrial robot can lead to severe injury from collisions with moving parts of the system. Conventional safety mechanisms therefore mostly restrict access to the robot using physical barriers such as walls and fences or non-contact protective devices including light curtains and laser scanners. As none of these mechanisms applies to human-robot-collaboration (HRC), a concept in which human and machine complement one another by working hand in hand, there is a rising need for safe and reliable detection of human body parts amidst background clutter. For this application camera-based systems are typically well suited. Still, safety concerns remain, owing to possible detection failures caused by environmental occlusion, extraneous light or other adverse imaging conditions. While ultrasonic proximity sensing can provide physical diversity to the system, it does not yet allow to reliably distinguish relevant objects from background objects.This work investigates a new approach to detecting relevant objects and human body parts based on acoustic holography. The approach is experimentally validated using a low-cost application-specific ultrasonic sensor system created from micro-electromechanical systems (MEMS). The presented results show that this system far outperforms conventional proximity sensors in terms of lateral imaging resolution and thus allows for more intelligent muting processes without compromising the safety of people working close to the robot. Based upon this work, a next step could be the development of a multimodal sensor systems to safeguard workers who collaborate with robots using the described ultrasonic sensor system.

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Metadaten
Document Type:Conference Object
Language:English
Parent Title (English):9th International Conference on Safety of Industrial Automated Systems, SIAS2018, 10-12 October, Nancy, France
First Page:49
Last Page:54
URL:http://www.inrs-sias2018.fr/index.php?langue=en&onglet=1&acces=&idUser=&emailUser=&messageConfirmation=
Publication year:2018
Tag:holography; human-robot collaboration; machine learning; ultrasonic sensor
Departments, institutes and facilities:Fachbereich Informatik
Institut für Sicherheitsforschung (ISF)
Dewey Decimal Classification (DDC):000 Informatik, Informationswissenschaft, allgemeine Werke / 000 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2018/11/10

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