Enabling robots to safely interact with humans is an essential goal of robotics research. The developments achieved over recent years in mechanical design and control made it possible to have active cooperation between humans and robots in rather complex situations. For this, safe robot behavior even under worst-case situations is crucial and forms also a basis for higher-level decisional aspects. For quantifying what safe behavior really means, the definition of injury, as well as understanding its general dynamics, are essential. This insight can then be applied to design and control robots such that injury due to robot-human impacts is explicitly taken into account. In this paper we approach the problem from a medical injury analysis point of view in order to formulate the relation between robot mass, velocity, impact geometry and resulting injury qualified in medical terms. We transform these insights into processable representations and propose a motion supervisor that utilizes injury knowledge for generating safe robot motions. The algorithm takes into account the reflected inertia, velocity, and geometry at possible impact locations. The proposed framework forms a basis for generating truly safe velocity bounds that explicitly consider the dynamic properties of the manipulator and human injury.

Enabling robots to safely interact with humans is an essential goal of robotics research. The developments achieved over the last years in mechanical design and control made it possible to have active cooperation between humans and robots in rather complex situations. In these terms, safe behavior of the robot even under worst-case situations is crucial and forms also a basis for higher level decisional aspects. In order to quantify what safe behavior really means, the definition of injury, as well as understanding its general dynamics are essential. This insight can then be applied to design and control robots such that injury due to robot-human impacts is explicitly taken into account. In this paper we approach the problem from a medical injury analysis point of view in order to formulate the relation between robot mass, velocity, impact geometry, and resulting injury qualified in medical terms. We transform these insights into processable representations and propose a motion supervisor that utilizes injury knowledge for generating safe robot motions. The algorithm takes into account the reflected inertia, velocity, and geometry at possible impact locations. The proposed framework forms a basis for generating truly safe velocity bounds that explicitely consider the dynamic properties of the manipulator and human injury

Zusammenfassung:In diesem Artikel befassen wir uns mit dem Problem eine für den Menschen sichere Robotergeschwindigkeit zu erzeugen. Hierfür untersuchen wir die Relation zwischen Kollisionsmasse, -geschwindigkeit und -geometrie, sowie der damit verbundenen Verletzung im medizinischen Sinne. Diese Einsichten werden derart repräsentiert, dass ein biomechanisch sicherer Geschwindigkeitsregler abgeleitet werden kann. Hierfür wertet der Algorithmus die reflektierte Trägheit, Geschwindigkeit und Oberflächengeometrie an möglichen Kollisionspunkten entlang der Roboterstruktur in Echtzeit aus. Abstract:In this paper, we approach the problem of generating human safe robot velocities. For this, we analyze the relation between robot mass, velocity, impact geometry, and resulting injury qualified in medical terms. We transform these insights into processable representations and propose a motion controller that utilizes injury knowledge for generating safe robot motions. For this, the algorithm takes into account the reflected inertia, velocity, and geometry at possible impact locations.