With the growing popularity of robots, the development of robot applications is subject to an ever increasing number of additional requirements from e.g., safety, legal and ethical sides. The certification of an application for compliance to such requirements is an essential step in the development of a robot program. However, at this point in time it must be ensured that the integrity of this program is preserved meaning that no intentional or unintentional modifications happen to the program until the robot executes it. Based on the abstraction of robot programs as workflows we present in this work a cryptography-powered distributed infrastructure for the preservation of robot workflows. A client composes a robot program and once it is accepted a separate entity provides a digital signature for the workflow and its parameters which can be verified by the robot before executing it. We demonstrate a real-world implementation of this infrastructure using a mobile manipulator and its software stack. We also provide an outlook on the integration of this work into our larger undertaking to provide a distributed ledger-based compliant robot application development environment.

In this transdisciplinary paper we discuss the question whether trust in human-robot-interaction (HRI) can be gained by gamification. Therefore, the concept of credibility will be introduced. A specific focus is on the question concerning the implementation of ethical rules in robotic safety systems. With a focus on Wittgenstein as a philosopher of technology we argue that in many fields of application cultural issues play a crucial role that cannot be controlled in a top-down approach. Instead, we follow a process-oriented bottom-up understanding of trust which pays attention to different social situations of normative practices. In order to combine our transdisciplinary philosophical and engineering points of view, a model for “gamifying trust” including ethical reflection as well as a short sketch of a possible technical implementation are presented

Modern robot systems are an essential technology for the digitalization of production and value-adding processes. The goal is to allow machines to operate in a common area with humans in so-called collaborative operation without separation by physical protective devices. This feature places particularly high demands on the fulfillment of robot safety, i.e., the safety of humans when handling the machine. This article focuses on the safe and reliable industrial use of mobile manipulators which are a combination of a mobile platform and a robot arm for object manipulation. The coordinated use of both robot systems enables a variety of new application scenarios and significantly increases flexibility. Mobile manipulators, however, pose complex challenges to their industrial integration as well as to safety and security in compliance with the legal and normative framework.

Today, visual sensor networks (VSNs) are pervasively used in smart environments such as intelligent homes, industrial automation or surveillance. A major concern in the use of sensor networks in general is their reliability in the presence of security threats and cyberattacks. Compared to traditional networks, sensor networks typically face numerous additional vulnerabilities due to the dynamic and distributed network topology, the resource constrained nodes, the potentially large network scale and the lack of global network knowledge. These vulnerabilities allow attackers to launch more severe and complicated attacks. Since the state-of-the-art is lacking studies on vulnerabilities in VSNs, a thorough investigation of attacks that can be launched against VSNs is required. This paper presents a general threat model for the attack surfaces of visual sensor network applications and their components. The outlined threats are classified by the STRIDE taxonomy and their weaknesses are classified using CWE, a common taxonomy for security weaknesses.

This paper discusses the need for a specialized vulnerability enumeration for robots and robot components and introduces the Robot Vulnerability Database (RVD)