ESMERA is going IROS and it will leave its mark in the event!
ESMERA will be hosting a workshop featuring some of the most innovative robotics SMEs in Europe. The workshop will consist of a series of targeted presentations from selected experiments participating in ESMERA, which will be available online. The online live session of the workshop will take place on September 27th 2021 from 14:00 to 16:00 CET. Each presentation will last approximately 15 minutes and will cover different industrial challenges and robotic solutions/technologies. This will be an interactive workshop mixing technical presentations, panel discussions as well as open floor exchanges, which will stimulate discussions around:
- Industrial challenges in several sectors such as Energy, Healthcare, Manufacturing, etc. will be addressed. The workshop will then explore the potential robotics and related digital technologies have for overcoming these challenges, including how this potential can be maximised.
- Novel robotic solutions and technologies will be showcased in presentations introducing results from ESMERA experiments.
- Scientific and technical aspects of developing robust solutions for the selected production domains will be shared.
- Demonstrations of newly developed and mature solutions that are ready for adoption in the robotics market will be made.
Our panel, which will include academics and practitioners, will engage in an open dialogue with the event’s attendees to discuss the milestones achieved so far and the key challenges to be addressed in the next 1, 5, and 10 years. Additionally, we will explore the potential of applying the presented solutions to address more applications/domains and promoting joint development activities in the fields of robotics using this workshop as a starting point. The last part of the workshop will host a networking session with the speakers and all participants to promote a further exchange of ideas and experiences, as well as joint activities to be undertaken in the future.
Programme of the online session
| Workshop ID | Start time | End time | Title | Speaker(s) | Session title |
| 2278 | 14:00 | 14:15 | ESMERA Project Presentation | George Michalos | ESMERA Project Presentation |
| 2278 | 14:15 | 14:30 | Challenges in Data Management and Solutions for Coping with high Volume and versatile Data Sources on the example of Data-based failure Prediction in Robotised Spot-Welding Applications by SUSPICION | Titanilla Komenda | ESMERA Industrial Challenges Presentation |
| 2278 | 14:30 | 14:45 | Manufacturing Challenge: Wire Harness Assembly Task | Žiga Gosar | ESMERA Industrial Challenges Presentation |
| 2278 | 14:45 | 14:55 | REFLECT: A solution for Robotized Material Manipulation and Assembly of Non-Rigid parts in the White Goods Industry | Andreas Sardelis | ESMERA Robotic Application and Technological Solutions |
| 2278 | 14:55 | 15:05 | ROMERO: Robots fOr extreMe EnviROnment | Vincenzo Calabrò | ESMERA Robotic Application and Technological Solutions |
| 2278 | 15:05 | 15:15 | ROVER4RT: Novel robotic solution for railway inspection and maintenance activities | Javier Sanchez Cubillo | ESMERA Robotic Application and Technological Solutions |
| 2278 | 15:15 | 15:25 | AEROWIND: Autonomous inspection of wind turbine blades by an Unmanned Aerial Vehicle | Stjepan Bogdan | ESMERA Robotic Application and Technological Solutions |
| 2278 | 15:25 | 16:00 | Panel discussion | Panel discussion and open floor |
Exhibition Participants
Autonomous inspection of wind turbine blades by an Unmanned Aerial Vehicle by AeroWind
Abstract: The focus of this presentation is showcasing a successful demonstration of state-of-the-art Unmanned Aerial Systems technologies in industrial environments. We will present a method for autonomous inspection of wind turbine blades performed by a UAV equipped with a LiDAR sensor and a high-resolution camera. Based on registration and matching of a wind turbine 3D model with acquired point cloud, the developed systems automatically generate and execute a UAV trajectory that guarantees an appropriate predefined distance from the blades, and at the same time, provides high-quality images of inspected surfaces.
FLOX-rover – Improving the lives of a trillion chickens! by FLOX
Abstract: FLOX is a livestock welfare company, combining machine learning, robotics and advanced sensing to help farmers automate previously manual processes, leverage rich data, and, with FLOX-rover – take high-value actions in the shed.
PRYSM – PRecision Sprayer Ground Robot by PRYSM
Abstract: Steep slope vineyards account for 10% – 12% of European viticultural land and produce some of the highest value wines. Row sizes are quite narrow, typically 90 – 150cm. Currently, where possible, treatments are applied from a small tractor-based system that employ an air-blast based system. Losses are high and ground compaction is a problem. Inspired by this problem, we developed a modular and precision terrestrial sprayer robot – the Precision Robotic Sprayer (PRySM) – capable of operating autonomously on rugged terrain with steep slopes and under the most diverse ground conditions. This robotic platform was adapted to work on hard terrain conditions and its dimensions and locomotion mechanism allow tight manoeuvring in the context of mountain vineyards with very narrow rows. This robot has advanced algorithms for self-localization and navigating using LiDAR and GNSS receiver data to support precision spraying tasks. PRYSM integrates a novel precision autonomous spray tool into the developed robotic platform. The PRYSM robot is being tested and validated in a real steep slope vineyard.
Robots fOr extreMe EnviROnment by ROMERO
Abstract: The ROMERO concept is a unique distributed system, ready to be deployed in extreme scenario environments to gather all the distributed sensors data and to support safety and civil protection officers involved in the monitoring and observation of volcanic activities. The ROMERO system includes an environmental data sensing system that continuously collects information about the surface and submerged areas through a weather station and a sea buoy, providing reliable and systematic data analysis, as well as abnormalities detection. In addition a web portal supports the decision making process, by providing access to data and historical data, while also giving access to the automatic engagement of aerial and underwater drones for field data collection.
ROVER4RT: Novel robotic solution for railway inspection and maintenance activities by ROVER4RT
Abstract: Rover4RT enables a cost-efficient solution to the challenging task of track inspection and vegetation management of railway infrastructure. The robot can assist in inspection and maintenance activities in the railway sector, yielding an efficient and versatile alternative to chemical herbicides and conventional inspection tasks. The robot enables performing infrastructure inspection activities (e.g. recording and streaming video about the rails’ status, sending pictures to the control centre, non-destructive inspection tests with ultrasounds), that are useful for railway operators and maintenance companies, while operating without stopping the rail traffic, therefore offering increased efficiency.
Moreover, given the incoming regulation by which herbicide glyphosates will be prohibited from the end of 2022, the system provides an alternative to chemical herbicides, carrying as payload a weed removal laser-based system able to detect and eliminate the weeds in a clean manner. The system is also designed to work without stopping rail traffic, operating between the railway tracks seamlessly while trains pass over its top. For this purpose, the robot is designed with a low height profile and width up to approx. 100 cm, so that it can move in between the railway tracks with trains passing overhead. A set of novel robotic arms have been developed to allow Rover4RT to engage itself firmly to the tracks, as a safety measure while a train passes. Each robotic arm is equipped with LIDAR equipment, which allows the detection of the track’s profile. Therefore the different geometries of side, fillet, web and base parts are discriminated and the robotic restraint arm knows how to approach and engage to the tracks. The robot will communicate through the ERTMS (European Rail Traffic Management System) to be aware of an approaching train, so as to deploy the restraint arms on time. This enables a continuous operation of the robot and spans further the possibilities for predictive maintenance, reducing the failure rate or failure frequency of the railway infrastructure and equipment.
The two main experiments of Rover4RT within ESMERA Phase I (namely, laser-based weed elimination and robotic engaging to railway tracks) have been conducted and successfully validated in a real railway scenario inside tracks in Navarra, Spain, with promising results. Specifically, the experimental outcomes validate the two innovations of Rover4RT: 1) the automated laser-based weeds’ growing prevention and removal system, and 2) the robotic safety track restraint system for railway maintenance robots. The integration of these two functionalities in a prototype demonstrator is also an achievement worth to be mentioned, capable of further maturing to pre-commercial levels and stepping over other robotic solutions currently proposed in the literature and/or available in the market.
SA3IR: Self-Adaptation for Augmented Autonomy in Intralogistics Robotics by SA3IR
Abstract: New navigation and cognitive abilities are motivating the introduction of robots in retail intra-logistics and also at their points-of-sale. MLAB has experience in providing robots for retails (e.g. the robot TORY for tracking inventory), being one of the partners of the Robotics4Retail initiative launched by the German EHI Retail Institute. In fact, MLAB has already developed a small autonomous low-lift pallet truck to move carts in factories of automotive suppliers. With the SA3IR proposal, MLAB wants to move one step forward and translate the product from factories to the retail scenario. Thus, the aim is the design and development of the whole framework needed to endow a fleet of small autonomous low lift pallet trucks with runtime adaptability to internal and external context changes. At a high-level, this framework should allow process optimization (e.g. routes chosen, absence of deadlocks), by correctly managing all data related to trucks and trolleys, warehouse layout, and operations requiring robots and humans. At a situational level, it should allow the re-planning of operations (e.g. runtime establishment of new unload points), and the local adaptation for robot subsystems (e.g. motion speed, people detection). For addressing these tasks, two academic partners are on the Consortium: UMA and UEX. MLAB and UMA have worked together on the design and development of a healthcare robot for interacting with elderly patients. On the other hand, in the context of the RobMoSys EU project, UEX and UMA have proposed novel approaches regarding self-adaptive robotics systems and, in particular, self-adaptation of high-performance and QoS-based middleware for robotics.
Challenges in Data Management and Solutions for Coping with high Volume and versatile Data Sources on the example of Data-based failure Prediction in Robotised Spot-Welding Applications by SUSPICION
Abstract: Even though the automotive industry is a highly optimized production sector, robotic spot-welding processes are still characterized by downtimes caused by tool contamination, cable breaks, communication errors of safety elements or errors due to clamping devices – to name a few. With the increasing developments in digitization and IIoT integration, a large amount of data can be recorded to identify the causes of the mentioned errors. However, data management is a highly challenging task – mainly due to data quality, volume and harmonization. In this workshop we present an overview of the different data sources of modern production facilities and challenges in data understanding. We focus especially on the challenges for the needed IT infrastructure to harmonize and use different data sources and volumes within a data management pipeline for applying machine-learning models in order to be able to predict production downtimes in robotic spot-welding applications based on available data and data sources.
Robotization of manufacturing laser cut components for the textile industry in high-mix low-volume production by Web2Print
Abstract: To increase productivity in the textile industry, more flexible automation solutions should be introduced for cutting and handling textile materials. Currently, the key advantages for European production are quality, trust, fast delivery times and customizability. Flexible automation, such as the Web2Print Garment solution, has the added benefit of reducing manufacturing costs through lower lead and setup times. The developed project is a cloud-based software which automatically combines orders into batches and generates ready work files for laser cutting machines. It also generates pick and place coordinates for robots on the fly. No laser or robot programming is needed on product or batch changes. Orders can be received in three different ways in the Web2Print system: from variable data, for example incoming from integrated factory MES / ERP system; from a partner in a subcontractor network; or from an online editor, which can be integrated for example with e-commerce sites, allowing mass customization. The robot can sort parts perfectly using the data and coordinates from the Web2Print system. This makes more complex and efficient nesting possible, as a larger amount of orders can used in optimization than possible with human operator. Also, locating objects is not dependent on lighting and machine vision which makes the system reliable, cost-efficient, and easy to use from an integrator‘s perspective. With a service business model, Web2Print can offer even small companies state-of-the-art technology affordably as SAAS. Also, with one cloud-based solution we can connect companies, create exciting new supply chains and enable distributed manufacturing.
REFLECT: A solution for Robotized Material Manipulation and Assembly of Non-Rigid parts in the White Goods Industry by REFLECT
Abstract: REFLECT is a robotic solution for the manipulation and assembly of non-rigid parts. It addresses inconsistencies of traditionally manual assembly operations by reducing the frequency of errors. The specially designed REFLECT end-effector ensures that the conversion from manual to robotized solutions can fulfill industrial process quality requirements through high dexterity at competitive cost. Fenceless and Safe Human-Robot Collaboration is employed through safety sensor-enhanced collaborative robots. REFLECT’s HMI boosts early adoption of the solution, while reducing setup and maintenance downtimes by enabling intuitive application programming, monitoring, and troubleshooting. The REFLECT solution is showcased at a white goods’ industrial paradigm, where a collaborative robot is used for inserting sealing rubber gaskets to dishwashers’ slots.
Design of human-centered collaborative assembly systems: the Wire Cobots project by Wire Cobots
Industrial collaborative robotics is one of the main enabling technologies of Industry 4.0. One of the main applications of collaborative robots will be the assistance of operators in the most physically stressful activities by reducing work-related biomechanical loads. The improvement of humans’ occupational well-being and the development of human-centered manufacturing systems is one of the main aims of the ongoing fourth industrial revolution. The factory of the future should focus on the implementation of smart and sustainable manufacturing systems, which consider the human as their core element. Improving manual assembly workstations by integrating collaborative solutions for the enhancement of operators’ ergonomics will be one of the main goals of the near future.
In this workshop, the transformation of a manual workstation for wire harness assembly into a collaborative and human-centered one is presented. The purpose is to present the result of ESMERA’s “Wire Cobots” project. The case study refers to the design of a collaborative workstation to improve the operators’ physical ergonomics while increasing productivity. Results demonstrate that the new collaborative assembly system provides valuable benefits for the operators’ working conditions as well as for the system’s production performance. In particular, the biomechanical load of the operator has been reduced by 12.0% for the right part and by 28% for the left part in terms of manual handling, and by 50% for the left part and by 57% for the right part in terms of working postures. Furthermore, the cycle time has been reduced by 12.3%.