The current utilization of multi-robot system (MRS) in industry and logistics has delineated a clear demarcation between tasks performed by humans and those by robots, often lacking efficient collaboration and adaptability. Despite their ability to perform numerous tasks, MRS are not sufficiently flexible, particularly in resilient and adaptive operations, which are crucial for dynamic industrial environments. As technology advances, the potential of MRS expands, yet the complexity and challenges within these systems also escalate. This underscores the need for a transformative approach in how these systems are integrated and managed to enhance not only their functionality but also their interaction within human-centric environments. One of the foremost challenges lies in developing systems that are not only resilient, adaptive, dynamic, and scalable but are also designed to transition from human support to automation in a modular fashion as technology and algorithms advance. This modular transition is designed to facilitate a seamless switch between robot and human operation. This includes using teleoperation as a method to bridge the gap when a situation demands human intervention or insight. The system should be equipped with decision-making capabilities to autonomously determine when it requires human assistance, depending on the complexity or unpredictability of the task at hand. Additionally, the system can learn from these human-led interventions, gradually incorporating human strategies and solutions into its algorithms to enhance future autonomous operations, thereby improving adaptability and resilience in dynamic environments. During the workshop, we will explore the potential to construct such systems through a smart orchestrating architecture. This architecture leverages various services in a modular manner, enhancing the flexibility of MRS and fostering a symbiotic relationship with human operators.
Organizers
evoBOT® is in the picture, the robot is created by the researchers at Fraunhofer Institute for Material Flow and Logistics, the affiliation of the organizers of the workshop, source: https://www.iml.fraunhofer.de/de/presse_medien/pressemifeilungen/LogiMAT2022_evoBOT.html
