Hastily formed knowledge networks and distributed situation awareness for collaborative robotics

Patrick Doherty,Piotr Rudol,Mariusz Wzorek,Cyrille Berger

doi:10.1007/s43684-021-00016-w

Abstract

In the context of collaborative robotics, distributed situation awareness is essential for supporting collective intelligence in teams of robots and human agents where it can be used for both individual and collective decision support. This is particularly important in applications pertaining to emergency rescue and crisis management. During operational missions, data and knowledge are gathered incrementally and in different ways by heterogeneous robots and humans. We describe this as the creation of Hastily Formed Knowledge Networks (HFKNs). The focus of this paper is the specification and prototyping of a general distributed system architecture that supports the creation of HFKNs by teams of robots and humans. The information collected ranges from low-level sensor data to high-level semantic knowledge, the latter represented in part as RDF Graphs. The framework includes a synchronization protocol and associated algorithms that allow for the automatic distribution and sharing of data and knowledge between agents. This is done through the distributed synchronization of RDF Graphs shared between agents. High-level semantic queries specified in SPARQL can be used by robots and humans alike to acquire both knowledge and data content from team members. The system is empirically validated and complexity results of the proposed algorithms are provided. Additionally, a field robotics case study is described, where a 3D mapping mission has been executed using several UAVs in a collaborative emergency rescue scenario while using the full HFKN Framework.

Highlights

The importance of effective communication and efficient data/knowledge transfer is essential for the coordination of life-saving activities in regions affected by natural or man-made disasters
Using Denning’s metaphor of Hastily Formed Networks for enhanced communication and conversation spaces among human agents in emergency rescue operations as a starting point, we extend the idea in two ways using the term Hastily Formed Knowledge Networks (HFKNs) as a guiding metaphor for this research
In [20], we present an extended version of an Resource Description Framework (RDF) Document, denoted RDF⊕ Document, that is given as input to the RDF Graph Synchronisation (RGS) System used to synchronize shared RDF Documents between agents

Summary

Introduction

The importance of effective communication and efficient data/knowledge transfer is essential for the coordination of life-saving activities in regions affected by natural or man-made disasters. 1.1 SymbiCloud HFKN framework The focus of this paper is the SymbiCloud HFKN Framework, which includes a data/knowledge management infrastructure that is intended to be used to support distributed, collaborative collection of data and knowledge and its shared use in multi-agent systems In this framework, each agent is assumed to have a SymbiCloud module (SCModule) containing its local or contextual perspective of its operational environment. Each agent is assumed to have a SymbiCloud module (SCModule) containing its local or contextual perspective of its operational environment This module can include geographically tagged information, sensor-data abstractions, 3D maps, static and dynamic object representations, and activity recognition structures, in addition to a rich set of reasoning engines and data/knowledge management processes. ROS/ROS2, but other aspects must be taken into account in the associated algorithms as will be shown

Contributions and content The paper includes the following contributions:

Conclusions