project . 2017 - 2021 . Closed


SMart rObOTs for fire-figHting
Open Access mandate for Publications
European Commission
Funder: European CommissionProject code: 734875 Call for proposal: H2020-MSCA-RISE-2016
Funded under: H2020 | MSCA-RISE Overall Budget: 909,000 EURFunder Contribution: 513,000 EUR
Status: Closed
01 Mar 2017 (Started) 28 Feb 2021 (Ended)
Open Access mandate
Research data: No

Over the years, changes in modern infrastructure have introduced new challenges to firefighting practices. Training and research programs have been developed to manage these challenges but there are still significant losses from fires each year. In 2013 alone, the fire departments in the USA responded to over 1.2 million fires which resulted in about 3,420 civilian fatalities, 15,925 injuries and property losses of about $12.4 billion dollars. In the UK, 192,600 fires responses, approximately 350 civilian fatalities, 10,300 injuries. The firefighting and rescue functions of the existing equipment and apparatus and their dexterity are limited, particularly in the harsh firefighting environments. The SMOOTH project aims to propose a novel robot-assisted decision making system in smart firefighting to perform searching and rescuing practice in the fire ground, and to facilitate the decision makings with higher efficiency. In the proposed system, a dexterous group of autonomous robots will be ingested, including an Octopus robot developed by SJTU with dexterous robotic upper body developed (with functions of high payload, forcible entry, excavation, obstacle avoidance and sweeping), a group of jumping robots invented by BU and YSU (with functions of obstacle avoidance) and a swarm of capsule systems invented by BU (with functions of precise positioning, narrow openings maneuveration and manipulation). A bunch of novel wearable and environmental sensors will be assembled and equipped on the robots and firefighter’s protection suits to facilitate the real-time machine-to-machine communications. A 3-D human-robot interactions infrastructure will be created to facilitate efficient interactions between human adaptive mechatronics and adaptive networked control. Based on these concepts, the consortium will investigate the needs and key technologies such as hybrid autonomous and miniaturized robotic modules, wireless sensor technologies, advanced decision support algorithms,

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