References of "Hochgeschwender, Nico 50015686"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailModel-Driven Interaction Design for Social Robots
Cornelius, Gary Philippe UL; Hochgeschwender, Nico UL; Voos, Holger UL

in Cornelius, Gary Philippe; Hochgeschwender, Nico; Voos, Holger (Eds.) 4th International Workshop on Model-driven Robot Software Engineering, Marburg, Germany, 2017 (2017, December)

Robotic software development frameworks lack a possibility to present,validate and generate qualitative complex human robot interactions and robot de-velopers are mostly left with unclear informal project ... [more ▼]

Robotic software development frameworks lack a possibility to present,validate and generate qualitative complex human robot interactions and robot de-velopers are mostly left with unclear informal project specifications. The devel-opment of a human-robot interaction is a complex task and involves different ex-perts, for example, the need for human-robot interaction (HRI) specialists, whoknow about the psychological impact of the robot’s movements during the in-teraction in order to design the best possible user experience. In this paper, wepresent a new project that aims to provide exactly this. Focusing on the interac-tion flow and movements of a robot for human-robot interactions we aim to pro-vide a set of modelling languages for human-robot interaction which serves as acommon, more formal, discussion point between the different stakeholders. Thisis a new project and the main topics of this publication are the scenario descrip-tion, the analysis of the different stakeholders, our experience as robot applicationdevelopers for our partner, as well as the future work we plan to achieve. [less ▲]

Detailed reference viewed: 20 (12 UL)
Full Text
Peer Reviewed
See detailA Perspective of Security for Mobile Service Robots
Cornelius, Gary Philippe UL; Hochgeschwender, Nico UL; Voos, Holger UL et al

in ROBOT'2017 - Third Iberian Robotics Conference, Seville, Spain, 2017 (2017, November 22)

Future homes will contain Mobile Service Robots (MSR) with diversefunctionality. MSRs act in close proximity to humans and have the physical capa-bilities to cause serious harm to their environment ... [more ▼]

Future homes will contain Mobile Service Robots (MSR) with diversefunctionality. MSRs act in close proximity to humans and have the physical capa-bilities to cause serious harm to their environment. Furthermore, they have sen-sors that gather large amounts of data, which might contain sensitive informa-tion. A mobile service robot’s physical capabilities are controlled by networkedcomputers susceptible to faults and intrusions. The proximity to humans and thepossibility to physically interact with them makes it critical to think about thesecurity issues of MSRs. In this work, we investigate possible attacks on mobileservice robots. We survey adversary motivations to attack MSRs, analyse threatvectors and list different available defence mechanisms against attacks on MSRs. [less ▲]

Detailed reference viewed: 48 (27 UL)
Full Text
See detailModel-Based Specification, Deployment and Adaptation of Robot Perception Systems
Hochgeschwender, Nico UL

Doctoral thesis (2017)

As robots are becoming ubiquitous and more capable, the need for introducing solid robot software development methods is pressing to increase robots' task spectrum. This thesis is concerned with improving ... [more ▼]

As robots are becoming ubiquitous and more capable, the need for introducing solid robot software development methods is pressing to increase robots' task spectrum. This thesis is concerned with improving software engineering of robot perception systems. The presented research employs a model-based approach to provide the means to represent knowledge about robotics software. The thesis is divided into three parts, namely research on the specification, deployment and adaptation of robot perception systems. The first part contributes the design and development of two domain-specific languages, namely RPSL and DepSL. Those languages provide suitable notations and abstractions to enable domain experts to express, compose and explore functional, architectural and deployment design decisions of robot perception systems. The resulting models are interpretable, thus they can be used not only to communicate design decisions to stakeholders, but also to verify them in an early development stage. The second part contributes means for deploying perception systems on real robot systems even in the presence of varying resource conditions. To this end, functional, architectural and deployment models are composed in a graph-structure. Such a graph enables not only humans, but also robots to derive implicitly defined information about their software both at design time and run time. The second part also contributes a reference architecture for deploying robot perception systems. The architecture provides a template solution for integrating not only the models required for deployment, but also all the other means required to carry out deployment. The third part utilizes both RPSL, DepSL and the reference architecture to specify, implement and evaluate three different robot perception systems. Those are capable to satisfy changing requirements induced, for example, by the robot's tasks or environment. This is achieved by proposing algorithms which derive adaptation actions based on models and varying requirements. [less ▲]

Detailed reference viewed: 37 (13 UL)
Full Text
Peer Reviewed
See detailGraph-based Software Knowledge: Storage and Semantic Querying of Domain Models for Run-Time Adaptation
Hochgeschwender, Nico UL; Schneider, Sven; Voos, Holger UL et al

in IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots SIMPAR, San Francisco, Dec 2016 (2016, December)

Software development for robots is a knowledge intensive exercise. To capture this knowledge explicitly and formally in the form of various domain models, roboticists have recently employed model-driven ... [more ▼]

Software development for robots is a knowledge intensive exercise. To capture this knowledge explicitly and formally in the form of various domain models, roboticists have recently employed model-driven engineering (MDE) approaches. However, these models are merely seen as a way to support humans during the robot's software design process. We argue that the robots themselves should be first-class consumers of this knowledge to autonomously adapt their software to the various and changing run-time requirements induced, for instance, by the robot's tasks or environment. Motivated by knowledge-enabled approaches, we address this problem by employing a graph-based knowledge representation that allows us not only to persistently store domain models, but also to formulate powerful queries for the sake of run time adaptation. We have evaluated our approach in an integrated, real-world system using the neo4j graph database and we report some lessons learned. Further, we show that the graph database imposes only little overhead on the system's overall performance. [less ▲]

Detailed reference viewed: 10 (4 UL)