ROBOTNIK

The objective of the project is the development of a mobile robot platform able to perform autonomous protection of critical infrastructures. This task is repetitive and labour-intensive, so it fulfils the basic requirements for its automation. This product addresses a huge global market that is already expecting important growth due to the maturing sensor and ICT technologies, that create new markets and business opportunities. Throughout the project, a detailed business plan will be elaborated. This business plan includes the following specific objectives: market study, strategy and implementation, SWOT analysis, revenue projections, manufacturing feasibility, user involvement, risk assessment, IP management, marketing plan (including distribution and sales channels) and study of the ability to increase profitability of the enterprise through ROBIN innovation.

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,

With the growing population and climate change, agricultural productivity growth is unlikely to meet the increased demand for food. Besides the increasing pressure to produce more, there is an overall need for higher quality and sustainable cultivation. Precision agriculture combined with intelligent robotic technologies can push to that direction. The incorporation of such technologies into agricultural production not only benefits productivity but also improves the working conditions of farmers and labourers. Intelligent systems are becoming the go-to solution to push towards precision agriculture, while a large number of farmer operations are already transitioning to full autonomy. Smart, automated and selective harvesting, in particular, can provide considerable improvement in production leaving the unripe product in the field to mature. However, in order to achieve such automation significant progress is required regarding the cognitive and mechatronic capabilities of the robotic agents replacing the human workers in these tasks, especially in cases where human-like actions are required by the robots. BACCHUS intelligent mobile robotic system promises to reproduce hand harvesting operations, while at the same time take the manual legwork out by autonomously operating in four different levels: i) performing robot navigation with quality performance guarantee in order to inspect the crops and collect data from the agricultural area through embedded sensorial system; ii) performing bi-manual harvesting operations with the needed finesse using a modular robotic platform, iii) employing additive manufacturing for adjusting the robot gripper to the geometry of the different crops, iii) presenting advanced cognitive capabilities and decision making skills. The envisioned system will be demonstrated and evaluated in the challenging vineyard environment inspecting different types of vines and harvesting bunches of grapes of different varieties in a human-like manner.

The emerging spring of Artificial Intelligence (AI) will enable innovative applications exploiting the myriad of connected sensors and appliances embedded in every corner of modern life. Currently, AI requires high computational resources only available in high-performance data centers; therefore, realizing an architecture capable of securely processing this unprecedented amount of remotely sensed and potentially sensitive data, as well as conveying timely responses to pervasive configurable actuators is a non-trivial endeavour, requiring the cooperation of multiple parties. To address these challenges, DECENTER aims to realise a robust Fog Computing platform, covering the whole Cloud-to-Things Continuum, that will provide AI application-aware orchestration and provisioning of resources. The project will enrich existing Cloud and IoT solutions with advanced capabilities to abstract features and process data closer to where it is produced. DECENTER will enable a collaborative environment in which multiple stakeholders (Cloud and IoT providers) can securely share and harmoniously manage resources, in dynamically created multi-cloud/edge, federated environments. Cross-border infrastructure federation will be realized via Blockchain-based Smart Contracts defining customized Service Level Agreements, used to commit the execution of verified workloads across multiple, potentially remote, administrative domains. Through such novelties, DECENTER will unlock the potential of innovative decentralised AI algorithms and models, by deploying them across multiple tiers of the infrastructure and federated clouds. The project will follow a lean implementation methodology and validate its concept with real-world pilots executed in urban, industrial and home environments. With its approach, DECENTER will target the emergence of innovative digital businesses, thus providing a competitive advantage to EU and Korean industry and fostering cross-border collaboration.