Overview

Mobile multi-robot systems gain increasing attention in research and industry. Among others, this development was driven by the fact that controlling these devices had become much easier recently through advanced electronics, miniaturization and thus more powerful onboard control systems, available at affordable prices. While applications in the domain of Search and Rescue (SAR) have profited from this development for years in a multitude of projects from different environments, the potential of multi-robot applications now is recognized in many other domains. These include environmental research, distributed surveillance of critical infrastructure, or dealing with major catastrophes (e.g., chemical accidents, flood, major fires), among others.

We identified common steps, relevant in all of these applications, and call them ScORe missions involving Search, continuously Observe and React tasks. Existing approaches have shown that ensembles of aerial robots (UAVs) and ground vehicles are suitable for coping with ScORe missions. However, those approaches often focus on isolated tasks of one ScORe mission or are tailored to particular applications. This specialization is necessary due to specific requirements to the robots’ capabilities in dedicated applications or environments. Besides different task requirements, the ensemble is faced with uncertainties when dealing with ScORe missions. Examples for common uncertainties are defects of robots at run-time, lack of clarity regarding the initial (environmental) setting the ensemble has to work in, and its development during run-time. These uncertainties make it hard to calculate a complete plan (including task scheduling and allocation) for each robot of the ensemble in advance. Complex ScORe missions clearly call for adaptation at run-time.

Our project aims at developing a reference system architecture for robot ensembles to handle such missions with focus on aerial robots and mobile ground vehicles. Therefore our project follows the idea of combining classic planning approaches with self-organization mechanisms to enable the robot ensemble to adapt to unforeseen changes in the ensembles as well as in the environment and to react appropriately, without time-intensive re-planning phases, and as autonomous as possible throughout all tasks of a ScORe mission. To equip a robot ensemble with the necessary degree of freedom, we propose to enhance existing modular hardware components with semantic knowledge, to make them self-aware. This allows the ensemble to reason about and optimize the current situation by initiating reconfigurations on the hardware and the software level at run-time.

Funded by

Key Facts

Start date:

01.07.2019

End date:

30.06.2022

Duration:

3 years