In the event of an emergency due to a fire or other crisis it is time consuming to establish whether the ground can be entered safely by human beings. The VIEW-FINDER project seeks to develop and utilise robots and an advanced base station for inspection and in-situ data gathering.
The robots will be installed with onboard TV/IR cameras, LADAR and other sensors to enhance scene reconstruction, as well as a wide array of chemical sensors. The data will be sent to the base station for processing and presented to the command of the operation combined with information originating from a web of sources. The information can also be forwarded to the relevant forces dealing with the crisis (e.g. fire fighters, rescue workers and police).
Besides the task specific sensors, 'conventional' sensors will support navigation. The robots will navigate individually or cooperatively by following high level instructions from the base station. The robots are made up of off-the-shelf units, including wheeled robots for the common fire ground and caterpillars for more exceptional circumstances. The robots will connect to the base station and to each other; using a wireless self-organising network of mobile communication nodes (that consist of other robots) which adapts to the terrain. The robots are intended to be used as the first explorers of the danger area, as well as to act as in-situ supporters and safeguards to human personnel.
The base station collects in-situ data and combines it with information retrieved from the large-scale GMES-information bases. It is equipped with a sophisticated human interface to display the information in a convenient and useable form to the human operators and operation command. The project will provide proof-of-concept solutions, to be evaluated by a board of End-Users, thus ensuring that all operational needs are addressed and accounted for. Project workshops that aim at further dissemination and exploitation of results will be organised.
Fields of science
Funding SchemeSTREP - Specific Targeted Research Project
50013 Campi Bisenzio
S70 2PQ Barnsley