[Th. 13/10, 10.30 – 11.00] I-RIM 3D and Institutional Welcome
[Th. 13/10, 11.00 – 12.00] Autonomous Mobile Robots – TH-M1
TH-M1-1 |
Implementation of path following and obstacle avoidance in omnidirectional platforms (nr. 2234) |
Authors | Simone Mentasti, Giulia Fasoli, Andrea Mauri and Matteo Matteucci |
Keywords | Path following, obstacle avoidance, AGV, mobile robotics |
Abstract | Mobile robots, in particular AGVs, have witnessed an increased interest in the last few years. This is due to the reduced costs and increased precision, which makes them highly advantageous in industrial applications like logistics. Depending on the operating scenario and constraints, this indoor robot can be built using different kinematic models (i.e., differential drive, omnidirectional, etc.). To best exploit each model’s advantage, different control and planning algorithms must be implemented. In this work, we propose a pipeline for path following and obstacle avoidance for omnidirectional robots. Our solution allows switching between different operating modes, simulating different kinematic models based on the scenario. The proposed system can achieve low error (i.e., less than 5cm) in the operating scenario |
TH-M1-2 |
An overview of global path planning methods for mobile robots for industrial applications (nr. 2312) |
Authors | Alessandro Bonetti, Lorenzo Sabattini and Simone Guidetti |
Keywords | Mobile robotics, Path planning, Environment Representation |
Abstract | This article presents an overview of one of the main problems in mobile robotics: path planning. It consists in finding a geometric collision-free path from a certain initial configuration to a final one. In particular, the global formulation requires the workspace to be fully known in order to generate a complete path avoiding obstacles before the robot begins its movement and, for this reason, the most well-known techniques of geometric representation of the environment are presented. |
TH-M1-3 |
The Marvin Project: an Omni-Directional Robot for Home Assistance (nr. 3033) |
Authors | Luigi Tagliavini, Andrea Eirale, Mauro Martini, Dario Gandini, Riccardo Silvestri, Marcello Chiaberge and Giuseppe Quaglia |
Keywords | assistive mobile robotics, artificial intelligence, autonomous robotics, vocal assistant, system design |
Abstract | In the last decades, many researchers are investigating how robotic solutions may be adopted to address the increasing need for home and personal assistance aggravated by current global challenges, e.g. population ageing and pandemic emergency. In this direction, the researchers at Politecnico di Torino, together with the colleagues from Edison S.p.A., developed the Marvin project which aims at designing a useful mobile robot for the domestic environment. In this work, the main features of the Marvin prototype and a first qualitative experimental validation are presented. |
TH-M1-4 |
Non linear model control for industrial robots (nr. 3040) |
Authors | Rocco Galati, Giacomo Mantriota and Giulio Reina |
Keywords | service robotics, path planner, nonlinear predictive control, industrial robots, autonomous navigation |
Abstract | In this article, the results of a nonlinear model predictive controller used to generate optimized trajectories for an omnidirectional industrial robot equipped with a spraying unit is presented. Results are provided for various trajectories along with consideration of controller performance. |
[Th. 13/10, 12.00 – 13.00] Human-Robot Interaction – TH-M2
TH-M2-1 |
Performance analysis of a tactile-based architecture for collaborative robots (nr. 1005) |
Authors | Francesco Grella, Francesco Giovinazzo, Alessandro Albini and Giorgio Cannata |
Keywords | Tactile Sensing, physical Human-Robot Interaction, Deep Learnin |
Abstract | Tactile sensors represent an intuitive and efficient interface for physical Human-Robot Interaction (pHRI). To ensure the safety of the human during industrial collaborative tasks we mounted four cylindrical-shaped handles, covered with the CySkin technology, over the gripper of an industrial manipulator, through which the operator can express his intention to physically interact. Tactile data are fed into a neural network that recognizes human touch during grasp, thus providing an enabling command for the control system. In this paper we present a performance analysis of the perceptual architecture based on distributed tactile sensors for Human-Robot Collaboration (HRC). The inference time comparison performed in this activity considers two computing architectures: a desktop workstation with a high-performance GPU and an embedded solution based on the NVIDIA Jetson Nano board. The inference time performance analysis also considers three different neural network optimization engines: Keras, TensorRT floating-point 16 and TensorRT floating-point 32. The results show that numerically optimized models allow to perform inference within the timing constraints even on the embedded architecture. An inference robustness analysis is also performed to verity if voluntary touch recognition fails when the user wears work gloves, showing negligible differences from bare-hand grasps. |
TH-M2-2 |
Robot Design Optimization for Human-Robot Collaborative Lifting Tasks (nr. 2545) |
Authors | Carlotta Sartore, Lorenzo Rapetti and Daniele Pucci |
Keywords | Ergonomy, Human-Robot-Interaction, Hardware Optimization, Humanoid Robots |
Abstract | Humanoid robots are foreseen to be soon part of our daily life, often interacting with humans. For this reason, several control architectures have been developed to address ergonomic physical human-robot interaction. However, the robot hardware design is yet to be considered as an element that can be optimized with respect to the collaborative task. This work presents a framework allowing to consider hardware parameters considering both hardware and ergonomic specific constraints. The proposed methodology is validated on the iCub humanoid robot considering the different scenario of payload lifting tasks. |
TH-M2-3 |
A Smart Workcell for Cooperative Assembly of Carbon Fiber Parts Guided by Human Actions (nr. 5003) |
Authors | Matteo Terreran, Stefano Ghidoni, Emanuele Menegatti, Enrico Villagrossi, Nicola Pedrocchi, Nicola Castaman, Alberto Gottardi, Christian Eitzinger, Giuseppe Salemi, Matteo Casubolo and Marcin Malecha |
Keywords | Human-robot cooperation, cooperative production, behaviour recognition, body pose estimation, human action recognition. |
Abstract | The production of carbon fiber parts is a complex process mainly performed by human operators. For small parts, high dexterity and skilled operators are needed while for large parts many people are often needed to transport the material without damaging it. The DrapeBot project aims at developing a human-robot cooperative system capable of assisting an operator working on carbon fiber parts. This requires environment perception in the workcell, intelligent robot task and motion planning, and the understanding of the production process. In particular, the project focuses on realizing a safe and effective collaboration where the operator can interact with the robot in an intuitive manner by means of gestures. This paper outlines the track proposed to create such an intelligent workcell. |
TH-M2-4 |
Collaborative workcell in industrial assembly process with online ergonomics monitoring (nr. 7763) |
Authors | Daniel Lanzoni, Francesca Negrello, Alessio Fornaciari, Gianluca Lentini, Stefano Ierace, Andrea Vitali, Daniele Regazzoni, Arash Ajoudani, Caterina Rizzi, Antonio Bicchi and Manuel Giuseppe Catalano |
Keywords | Ergonomics, Collaborative Robots, Remote Monitoring, Motion-Capture System |
Abstract | With the advent of Industry 4.0, new technologies are introduced to provide welfare beyond jobs and growth, such as collaborative robots. To be effective, the collaboration between human and robot should be safe, intuitive and stable. Safe collaboration does not only means avoiding human-robot contact, the operator must also feel confident during the collaboration with the robot and avoid incorrect postures (physical ergonomics). In this work, we analyzed an industrial use-case related to the automation of manual tasks in production processes. We propose a collaborative workcell design which integrates a solution to real-time remote control of operator’s ergonomics in an interactive environment. The platform is tested in a real use case that involves several mechanical tasks in different scenarios, with and without the support of the robot. The results show both improvements in operator’s working condition when supported by robots and overall in the efficiency of the process. |
[Th. 13/10, 13.00 – 14.00] Lunch break
[Th. 13/10, 14.00 – 15.00] Intuitive Programming and Task & Motion Planning 1 – TH-A1
TH-A1-1 |
Towards An Effective Human-Robot Team Collaboration – A Resilient Task Scheduling Approach For Real Industrial Scenarios (nr. 242) |
Authors | Andrea Pupa, Wietse Van Dijk, Christiaan Brekelmans and Cristian Secchi |
Keywords | HRC, human-centered robotics, task planning. |
Abstract | Dynamic task scheduling between human and robots is one of the great challenges of collaborative robotics. The high dynamism of the shared workspace brings many uncertainties that cannot be foreseen on beforehand. Therefore, an offline task scheduling strategy leads to really poor performance in such contexts. In this paper, an approach to achieve a resilient and reliable task scheduling is presented. The proposed framework can deal with deviations during operation, different operator skills, errors and substitution of actors. |
TH-A1-2 |
A CAE-based Tool for Energy-Optimal Trajectory Planning in Automatic Machines (nr. 3135) |
Authors | Giovanni Berselli, Federico Balugani and Claudio Melchiorri |
Keywords | Servo-Mechanisms, Virtual Prototyping, Trajectory comparison, Eco-Design Methods, CAD/CAE tools |
Abstract | Position-controlled Servo-Mechanisms, commonly referred to as electronic cams, are widely employed in automatic machines in order to increase flexibility and versatility. Nonetheless, at the state-of-the-art, these mechatronic devices are still sub-optimized when energy consumption is considered as a performance metric. In fact, the industrial scenario is missing not only energy-efficient hardware (available though cost ineffective), but also virtual prototyping platforms allowing to effectively compute energy-optimized motions. In this context, the purpose of the present abstract, is to introduce a CAE-based tool, conceived with non-experts in mind, that allows to determine energy-optimal point-to-point trajectories, starting from a virtual model of the servo-system, built in a Computer-Aided-Engineering environment. |
TH-A1-3 |
Enabling intuitive smart programming in industrial processes (nr. 5535) |
Authors | Gianluca Lentini, Francesca Negrello, Marc Galusi, Giorgio Grioli, Stefano Ierace, Antonio Bicchi and Manuel Giuseppe Catalano |
Keywords | Learning from Demonstration, smart programming, flexible manufacturing. |
Abstract | Today robotics offers robust and sophisticated hardware solutions that are leading the market to mass production. However, the high demand for small batches of highly customized products requires flexible processes, and the considerable cost of programming robotic systems induces many companies to still rely on manual labor even for low value-added tasks. In this context, Learning from Demonstration (LfD) has established as a promising method for transferring capabilities from humans to robots. This paper proposes a programming framework that allows non-expert users to intuitively program a robotic system for a product testing task. Finally, we validated our approach in both a simulated environment and real-world use cases. |
TH-A1-4 |
Robotic Autonomous Loco-Manipulation For Logistics In Industrial Plants (nr. 7743) |
Authors | Alessandra Duz, Francesca Negrello, Luca Paludo, Davide Benvenuti, Alessandro Palleschi, Elisa Stefanini, Stefano Ierace, Nikos Tsagarakis, Lucia Pallottino, Antonio Bicchi and Manuel G. Catalano |
Keywords | Autonomous manipulation in constrained environment, logistics, technology transfer, navigation. |
Abstract | The machine tending in a productive plant typically requires the transport of material from a storage area to a productive area. The plant logistics phase is a part of the production process that is often performed manually, due to the technological challenges related to the manipulation of objects in constrained environments, such as the shelf of a warehouse. However, an effort for its automation is justified by the fact that for an human operator this activity is fatiguing, not ergonomic and with low added value. This paper proposes a control framework for the automation of plant logistics for an industrial case study, integrating navigation and objects manipulation. |
[Th. 13/10, 15.00 – 16.00] Round table “State of the Art and Trends in Industrial Robotics”
[Th. 13/10, 16.00 – 16.30] Coffee break
[Th. 13/10, 16.30 – 17.45] Intuitive Programming and Task & Motion Planning 2 – TH-A2
TH-A2-1 |
SmartOffline NextGen: SW Architecture and Applications (nr. 1502) |
Authors | Matteo Ragaglia, Nicola Battilani, Antonio Castellano, Silvia Costi, Joao Marcos Da Silva Araujo, Cesare Fantuzzi, Angela Grasso, Gabriele Masotti, Mirko Mattioli, Giorgio Motta and Umberto Scarcia |
Keywords | robot programming, offline programming |
Abstract | Today robots represents a key factor in several industry fields as far as productivity and competitiveness are concerned. To this purpose, offline programming approaches and tools are clearly needed in order to allow fine development and fast adaptation of robot programs while minimizing machine downtime. In this context, this work introduces the offline programming software developed by SACMI in collaboration with IT-I, named “SmartOffline NextGen”. |
TH-A2-2 |
SmartKit: an Architecture for Modelling Complex Industrial Tasks (nr. 6196) |
Authors | Niccolo Lucci, Mattia Marconi, Oscar Ferrato, Andrea Monguzzi, Andrea Maria Zanchettin and Paolo Rocco |
Keywords | Semantics for robots, Human-robot collaboration, Architecture for smart robotics |
Abstract | The interest in collaborative robotics applications keeps increasing with the advancing of the years. Such growth is due to the robot’s flexibility in the production line and to the interactions that may happen with the human partner. However, human-robot collaboration is far from being adopted in practice, especially for complex industrial applications such as assembly tasks. This work formalises an architecture that models human and robot workflows and synchronises their activities, spots errors during the human task execution, and notifies the operator that something unexpected happened. The system has then been tested in an industrial collaborative assembly operation. |
TH-A2-3 |
Learning from demonstrations without parameter tuning for an industrial cobot (nr. 7480) |
Authors | Lorenzo Panchetti, Jianhao Zheng, Mohamed Bouri, Nicola Ischia and Malcolm Mielle |
Keywords | Learning from demonstrations without parameter tuning for an industrial cobot |
Abstract | State-of-the-art learning from demonstration (LfD) methods for collaborative robots—skill transfer and generalization through a set of demonstrations—require manually tuning intrinsic parameters. Hence, LfD cannot be used readily in industrial contexts without experts. We propose a parameter-free method based on probabilistic movement primitives, where all the parameters are pre-determined using Jensen-Shannon divergence and Bayesian Optimization method, so users do not perform any tuning. This method learns motions from a small dataset of user demonstrations, and generalizes the motion to various scenarios and conditions with no manual tuning. We evaluate our method in field tests where the cobot works with Schindler workers in the field. We show errors between the cobot end-effector and target positions ranging from 0 to 1.479±0.351mm, and no task failures for all tests. Questionnaires completed by Schindler workers highlighted our method’s ease of use, feeling of safety, and the accuracy of the reproduced motion. |
TH-A2-4 |
Towards Robot Avatars in Industrial Applications (nr. 8062) |
Authors | Francesca Negrello, Lorenzo Vergani, Silvia Ottaviani, Mario Corsanici, Angelo Iapichino, Gianluca Lentini, Alessandra Duz, Stefano Ierace, Giorgio Grioli, Nikos Tsagarakis, Antonio Bicchi and Manuel Giuseppe Catalano |
Keywords | robot avatar, metaverse, telexistence, technology transfer. |
Abstract | In the last years power computing and communication technologies have improved greatly, while at the same time immersive and wearable user interfaces became available at a consumer level. The widespread of these technologies fostered research in the field of telexistence and robot avatars, making it mature enough to be deployed out of the lab. There is a general consensus that enabling the remotization of physical activities would have a large impact on both safety and effciency of industrial processes. In this paper we report our work towards the development of robot avatars for industrial applications and the preliminary results of their deployment in real use cases. |
TH-A2-5 |
A Smart Workcell for Automatic Pick and Sorting for Logistics (nr. 8626) |
Authors | Nicola Castaman, Alberto Gottardi, Emanuele Menegatti and Stefano Tonello |
Keywords | instance segmentation, artificial intelligence, industrial robotics, vision system, workcell, logistics |
Abstract | Vision guided robots are enjoying growing success in industry, thanks to their adaptability to unstructured contexts and applications. In typical bin-picking applications, a robot is guided to pick known rigid objects randomly placed inside a container. Given the objects’ CAD models, it is possible to accurately estimate the object pose and to perform the grasp synthesis in a closed form. Unfortunately, in logistics, as in many other sectors, robotcs are required to manipulate polymorphic and deformable objects. In this work, we present a complete robotized pick and place solution for logistics able to address these challenges related to the variability of shapes of the objects. It exploits a model-less data-driven approach to bin-picking to detect boxes and parcels both randomply placed in containers or palletized. The proposed system will be easily adaptable to a wide range of applications, thus greatly improving its potential impact. |
[Th. 13/10, 17.45 – 17.50] Closure of the first day
[Fr. 14/10, 10.30 – 11.00] Keynote Speech
[Fr. 14/10, 11:00 – 12.00] Intelligent Robots and Machines for High-Performance Processes – FR-M1
FR-M1-1 |
Industrial Manipulator Parametric Identification (nr. 669) |
Authors | Mariapaola D’Imperio, Rajesh Suburraman and Ferdinando Cannella |
Keywords | Flexible joints, Modelling errors, Manipulators |
Abstract | Abstract. High precision industrial applications call for equally precise functioning of industrial manipulators, which in turn requires accurate modeling of the manipulators. This paper carries out a detailed study on the modeling of industrial manipulators with elastic joints to improve their accuracy. In particular, the effect of adopting a simple harmonic drive (HD) model and ignoring a dynamic effect called low inertia coupling between the actuators and links on the model accuracy has been analyzed from a parameter estimation perspective. Since the aforementioned model characteristics have been generally ignored for high gear reduction ratios, this study is carried out with five different reduction ratios ranging from low to high, where three different models of a three-joints elastic manipulator are considered. The accuracy of the models is compared using the torque performance metrics of a predefined joint motion of the robot. Furthermore, the impact of the models with different accuracy is assessed by carrying out a state-of-the-art dynamic parameter estimation, and the resulting errors are compared to ascertain the merits of adopting a detailed elastic dynamic model of a manipulator. |
FR-M1-2 |
Integrated Robot Motion and Process control for manufacturing reshaping (nr. 2739) |
Authors | Andrea Crosato, Daniele Colombo, Maurizio Motta, Fabio Guaglione, Stefano Mutti, Nicola Pedrocchi, Lorenzo Molinari Tosatti, Valntina Furlan, Ali Gökhan Demir and Barbara Previtali |
Keywords | Robotic Processes |
Abstract | The future of metal manufacturing processes like laser cutting, welding, and additive manufacturing shall rely on intelligent systems spearheaded by Industry 4.0. Such a digital innovation is indeed driving machinery builders to a profound transformation. From custom machines designed and optimized for a specific process, the ambition is to exploit the openness and the large availability of industrial robots to increase flexibility and reconfigurability of multi processes implementations. The challenge is that machinery builders transform themselves into high-knowledge specialized process-driven robot integrators, able to optimize the robot motion with the process controller leveraging on intelligent sensing and cognition. The work describes the multi-annual collaboration of the BLM group and Politecnico di Milano, with the support of CNR, focused on the deployment of a complete working robotic workstation characterized by the full integration of the robot control and motion planning with manufacturing processes. |
FR-M1-3 |
Thermal effects in identifying the dynamic parameters of an industrial robot (nr. 5893) |
Authors | Roberto Pagani, Giovanni Legnani, Monica Tiboni, Riccardo Adamini and Manuel Beschi |
Keywords | Robot Dynamics; Friction; Temperature |
Abstract | This work describes the influence of temperature on the identification of the dynamic model of an industrial manipulator. The tests show that the joint friction changes during the robot operation. The variation is due to the heat generated by friction. A model is used to estimate the temperature and related friction variation. Experimental data collected on an industrial robot are discussed. Repetitive tests performed on different days showed that the inertial and friction parameters can be robustly estimated. |
FR-M1-4 |
Physic-informed machine learning for centerless grinding optimization (nr. 6214) |
Authors | Marco Leonesio, Riccardo Pessina and Giacomo Bianchi |
Keywords | Centerless grinding, intelligent machine, physicinformed machine learning |
Abstract | Centerless grinding is a machining process characterized by highly nonlinear dynamics, large model uncertainty and considerable sensitivity to process parameters. Guaranteeing quality of the worked parts, basically roundness, and short processing time by an optimal process setup is typically a specialized and time-consuming task. In this work, an approach is presented for centerless grinding parameters setup and optimization based on physic-informed machine learning techniques. The real data for model training are provided both as measurements on the ground workpieces and as on-line monitoring signals. The developed functionalities concur in implementing the concept of “intelligent grinding machine”, proposed by Monzesi srl, an innovative SME operating in machine tools sector. |
[Fr. 14/10, 12:00 – 13.00] Intelligent Sensing and Methods for Intelligent Machines – FR-M2
FR-M2-1 |
PROPHET: PReference-based OPtimization for Human-cEnTric visual inspection (nr. 2543) |
Authors | Marco Maccarini, Loris Roveda, Nicola Castaman and Dario Piga |
Keywords | Human-centric production, human-robot collaboration, human-robot interaction, knowledge transfer, preference-based optimization, artificial intelligence |
Abstract | The aim of this project (PROPHET) is to develop a visual inspection system able to automatically configure the control parameters, learning from the choices made by an expert operator. The resulting system will allow the adoption of automated visual inspection even in complex inspection tasks and reduce the setting up time by learning from skilled operators inspection results based also on their experience. The developed system will be tested in the inspection of 3 parts from different sectors (e.g., automotive and aerospace industry), evaluating its performance in comparison with manual and robotized inspections. |
FR-M2-2 |
Tactile based robotic skills for optimal cable grasping and cable contour following (nr. 5874) |
Authors | Andrea Monguzzi, Martina Pelosi, Francesco Alberti, Andrea Maria Zanchettin and Paolo Rocco |
Keywords | Deformable linear object, DLO tactile based manipulation, DLO grasping, DLO contour following |
Abstract | The robotic manipulation of deformable linear objects (DLOs) such as cables is currently a challenge. In this work, we propose a set of skills based on data from tactile sensors mounted on the end effector fingertips to allow the robot to optimally grasp a DLO and follow its contour. These skills are applied to perform a wiring operation. |
FR-M2-3 |
Edge architecture for cooperative mobile manipulators handling and planning (nr. 6401) |
Authors | Stefano Mutti, Nicola Pedrocchi, Vito Renò and Nicola Gallo |
Keywords | Mobile manipulators, cooperative planning, distributed control, cloud computing, computer vision |
Abstract | Mobile manipulators have been getting employed in industrial scenarios more often in recent years. This is due to their huge dexterity, the high amount of degree of freedom, and their ability to move freely in the working space. Having a huge redundancy makes it difficult for the planning algorithm to devise a plan, especially when multiple mobile robots are involved and their navigation is constrained. On the other hand, the robotic arm mounted on top can compensate for the navigation path following errors, but require prompt error estimation and low communication latency in the whole system. |
FR-M2-4 |
ARGO: Autonomous inspection of RollinG stOcks (nr. 8854) |
Authors | Luca Tiseni, Massimiliano Gabardi, Davide Giovanni Garbin, Domenico Chiaradia, Daniele Leonardis, Massimiliano Solazzi and Antonio Frisoli |
Keywords | Condition based maintenance, inspection, robotics, rolling stocks |
Abstract | In the field of the condition based maintenance, the ARGO robot is a railway inspection platform designed to move under the trains, both on standard and elevated tracks, in order to collect high quality visual data of critical components. Train inspection is usually performed by human personnel in dedicated facilities, equipped with inspection pits. The peculiar ability of ARGO to operate on conventional railway tracks extends the inspection capabilities outside the conventional maintenance plants, with the potential to significantly change costs, time and frequency of the inspections. The proposed system can both perform autonomous inspection or be remotely teleoperated by using the operator control interface, including software functionalities to store and generate the final inspection report. The system has been already evaluated in two different train inspection facilities, and also operated directly by on-field inspection personnel. |
[Fr. 14/10, 13.00 – 14.00] Lunch break
[Fr. 14/10, 14.00 – 15.00] New Robots and Systems for New Markets – FR-A1
FR-A1-1 |
Towards Accurate 3D Positioning in Large-Scale Underwater Environments (nr. 3507) |
Authors | Daniele Evangelista, Ivano Donadi, Daniel Fusaro, Emilio Olivastri, and Alberto Pretto |
Keywords | Marine Robotics, Range Sensing, Vision-Based Navigation, Localization |
Abstract | An effective and reliable AUV (autonomous underwater vehicle) should be capable to carry out complex underwater maintenance and exploration tasks in complete autonomy. Unfortunately, the hostility of the underwater environment, combined with the lack of any communication infrastructure and global positioning, introduce important scientific challenges. In this paper, we introduce an underwater global positioning system for AUVs suitable for large-scale environments sparsely populated by man-made infrastructure. Our system relies on sonar and stereo camera data, by means of a novel deep descriptor for sonar images and a two-view pixel-wise voting network for 6DoF (Six degrees of freedom) object pose estimation, both trained on synthetically generated datasets. The global AUV position is then estimated by exploiting a probabilistic framework that fuses on-line the available sensor readings. |
FR-A1-2 |
First Steps Towards a Cable-Driven Parallel Robot for Naval Operations (nr. 6740) |
Authors | Edoardo Idà, Michele Angelini, Marco Carricato, Daniele Bertin, Vincenzo Orassi, Enrico Mantovani and Davide Bazzi |
Keywords | Cable-driven parallel robots, marine robots, sea robots, winches |
Abstract | This paper focuses on the study of a cable-driven parallel robot (CDPR) for the automated handling of payloads from a ship. Handling operations are performed at sea, under calm to mild weather conditions, thus both the payload and the ship (on which the robot is installed) may possess oscillatory motions. The tasks the robot has to perform are (i) payload autonomous tracking and picking on the sea surface, and (ii) payload lifting. Robot and task modelling are introduced, as well as the controllers used to achieve such operations. |
FR-A1-3 |
Progress in artificial components for multisource energy harvesting with living plant leaves (nr. 7910) |
Authors | Fabian Meder, Serena Armiento and Barbara Mazzolai |
Keywords | Energy, sustainability, bio-inspired robotics |
Abstract | To which extent devices or machines could be constructed by biodegradable or even living components is a crucial question for the sustainable transition of technology. We showed that living plants (instead of dead, plant-derived materials) provide structures and materials that can be used in high-tech devices such as energy harvesters and sensors. Here, we summarize our recent results on exploiting living plants and their materials in plant-hybrid energy harvesters, in which the plant is used to convert a mechanical energy such as from leaves fluttering in the wind and rain drops, and, acting as antenna, to convert radio frequency radiation into electricity. This is realized by modifying the plant with soft artificial materials that do not harm the tissue. |
FR-A1-4 |
Towards the digitalization of upper limbs rehabilitation: integration of a functional calibration procedure and usability study. (nr. 8595) |
Authors | Camilla Larini, Silvia Sciamanna, Gabriele Ceruti, Giuseppe Recchia, Francesca Salaorni, Marialuisa Gandolfi, Michele Tinazzi, Federico Schena, Pietro Garofalo, Michele Raggi and Alice Ravizza |
Keywords | Digital Rehabilitation, IMU, Serious Games, Usability, Neuro-motor Disorders, Functional Calibration. |
Abstract | . Since neuro-motor disorders have a primary relevance, rehabilitative therapies supported by medical devices are needed. The combination of serious games and IMUs is promising: this work focuses on a digital device allowing the patients to perform rehabilitation for upper limbs at home, for which integration of a functional calibration procedure to compensate the STS misalignment, a validation study, and a usability study were implemented. Results have revealed a general willingness to use the device and these findings will be used for the development of a new digital rehabilitation system. |