Trust Repair in Human-Swarm Teams+

Swarm robots are coordinated via simple control laws to generate emergent behaviors such as flocking, rendezvous, and deployment. Human-swarm teaming has been widely proposed for scenarios, such as human-supervised teams of unmanned aerial vehicles (UAV) for disaster rescue, UAV and ground vehicle cooperation for building security, and soldier-UAV teaming in combat. Effective cooperation requires an appropriate level of trust, between a human and a swarm. When an UAV swarm is deployed in a real-world environment, its performance is subject to real-world factors, such as system reliability and wind disturbances. Degraded performance of a robot can cause undesired swarm behaviors, decreasing human trust. This loss of trust, in turn, can trigger human intervention in UAVs' task executions, decreasing cooperation effectiveness if inappropriate. Therefore, to promote effective cooperation we propose and test a trust-repairing method (Trust-repair) restoring performance and human trust in the swarm to an appropriate level by correcting undesired swarm behaviors. Faulty swarms caused by both external and internal factors were simulated to evaluate the performance of the Trust-repair algorithm in repairing swarm performance and restoring human trust. Results show that Trust-repair is effective in restoring trust to a level intermediate between normal and faulty conditions

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

Wireless Sensor Technology Selection for I4.0 Manufacturing Systems

The term smart manufacturing has surfaced as an industrial revolution in Germany known as Industry 4.0 (I4.0); this revolution aims to help the manufacturers adapt to turbulent market trends. Its main scope is implementing machine communication, both vertically and horizontally across the manufacturing hierarchy through Internet of things (IoT), technologies and servitization concepts. The main objective of this research is to help manufacturers manage the high levels of variety and the extreme turbulence of market trends through developing a selection tool that utilizes Analytic Hierarchy Process (AHP) techniques to recommend a suitable industrial wireless sensor network (IWSN) technology that fits their manufacturing requirements.In this thesis, IWSN technologies and their properties were identified, analyzed and compared to identify their potential suitability for different industrial manufacturing system application areas. The study included the identification and analysis of different industrial system types, their application areas, scenarios and respective communication requirements. The developed tool’s sensitivity is also tested to recommend different IWSN technology options with changing influential factors. Also, a prioritizing protocol is introduced in the case where more than one IWSN technology options are recommended by the AHP tool.A real industrial case study with the collaboration of SPM Automation Inc. is presented, where the industrial systems’ class, communication traffic types, and communication requirements were analyzed to recommend a suitable IWSN technology that fits their requirements and assists their shift towards I4.0 through utilizing AHP techniques. The results of this research will serve as a step forward, in the transformation process of manufacturing towards a more digitalized and better connected cyber-physical systems; thus, enhancing manufacturing attributes such as flexibility, reconfigurability, scalability and easing the shift towards implementing I4.0