Collision analysis and safety evaluation using a collision model for the frontal robot–human impact

The safety analysis of human–robot collisions has recently drawn significant attention, as robots are increasingly used in human environments. In order to understand the potential injury a robot could cause in case of an impact, such incidents should be evaluated before designing a robot arm based o...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Robotica 2015-08, Vol.33 (7), p.1536-1550
Hauptverfasser: Park, Jung-Jun, Song, Jae-Bok, Haddadin, Sami
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The safety analysis of human–robot collisions has recently drawn significant attention, as robots are increasingly used in human environments. In order to understand the potential injury a robot could cause in case of an impact, such incidents should be evaluated before designing a robot arm based on biomechanical safety criteria. In recent literature, such incidents have been investigated mostly by experimental crash-testing. However, experimental methods are expensive, and the design parameters of the robot arm are difficult to change instantly. In order to solve this issue, we propose a novel robot-human collision model consisting of a 6-degree-of-freedom mass-spring-damper system for impact analysis. Since the proposed robot-human consists of a head, neck, chest, and torso, the relative motion among these body parts can be analyzed. In this study, collision analysis of impacts to the head, neck, and chest at various collision speeds are conducted using the proposed collision model. Then, the degree of injury is estimated by using various biomechanical severity indices. The reliability of the proposed collision model is verified by comparing the obtained simulation results with experimental results from literature. Furthermore, the basic requirements for the design of safer robots are determined.
ISSN:0263-5747
1469-8668
DOI:10.1017/S0263574714000137