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arXiv 2024年

作者： Chen, Zixi Ren, Xuyang Hamamatsu, Yuya Ciuti, Gastone Stefanini, Cesare Biorobotics Institute The Department of Excellence in Robotics and AI Scuola Superiore Sant’Anna Pisa56127 Italy Multi-scale Medical Robotics Centre Chow Yuk Ho Technology Centre for Innovative Medicine The Chinese University of Hong Kong Hong Kong Department of computer systems Tallinn University of Technology Tallinn Estonia

The nonlinearity and hysteresis of soft robot motions have posed challenges in control. The Jacobian controller is transferred from rigid robot controllers and exhibits conciseness, but the improper assumption of soft robots induces the feasibility only in a small local area. Accurate controllers like neural networks can deal with delayed and nonlinear motion, achieving high accuracy, but they suffer from the high data amount requirement and black-box property. Inspired by these approaches, we propose an adaptive generalized Jacobian controller for soft robots. This controller is constructed by the concise format of the Jacobian controller but includes more states and independent matrices, which is suitable for soft robotics. In addition, the initialization leverages the motor babbling strategy and batch optimization from neural network controllers. In experiments, we first analyze the online controllers, including the Jacobian controller, the Gaussian process regression, and our controller. Real experiments have validated that our controller outperforms the RNN controller even with fewer data samples, and it is adaptive to various situations without fine-tuning, like different control frequencies, softness, and even manufacturing errors. Future work may include online adjustment of the controller format and adaptability validation in more scenarios. Copyright © 2024, The Authors. All rights reserved.

关键词： Pneumatic control equipment

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Towards a Soft Artificial Larynx: A Biomimetic Design 12th

Towards a Soft Artificial Larynx: A Biomimetic Design

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Proceedings of the 12th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2023

作者： Pozzi, Jasmine Conte, Arianna Maselli, Martina Marchese, Maria Raffaella Nacci, Andrea Cianchetti, Matteo The BioRobotics Institute Scuola Superiore Sant’Anna Pisa Italy The Department of Excellence in Robotics and AI Scuola Superiore Sant’Anna Pisa Italy Unità Operativa Complessa di Otorinolaringoiatria Dipartimento di Neuroscienze Organi di Senso e Torace Fondazione Policlinico Universitario A. Gemelli IRCSS Rome Italy ENT Audiology and Phoniatrics Unit University Hospital of Pisa Pisa Italy

ISBN: (纸本)9783031395031

The larynx is one of the smallest but also one of the most complex organs in the human body, with three main functions: breathing, swallowing, and phonation. In case of total laryngectomy, all these functions are missing. Currently, they are replaced with a tracheal stoma and a vocal prosthesis, which give many physical and social problems to the subject. The long-term aim of this work is to create an implantable artificial larynx, able to reproduce all the larynx functions. Here, we present the first steps toward the creation of the artificial organ. We analyzed the larynx of different animal classes, to find basic structures and movements, shared among all the Tetrapoda. We used these models as a guide for simplifying the human larynx to obtain a functional design. We found that two cartilages (i.e., the cricoid and the arytenoids) and three muscles (i.e., the posterior cricoarytenoid, the lateral cricoarytenoid, and the thyroarytenoid) are common to all the studied species. Based on this, we proposed a larynx design, suggesting also possible materials, whose validity will be tested in the near future. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Artificial organs

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Edge ai Algorithm for FBG-Based E-Skin Touch Localization on Embedded Electronics

Edge AI Algorithm for FBG-Based E-Skin Touch Localization on...

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IEEE SENSORS

作者： Elisabetta Leogrande Francesco Dell'Olio Stefano Mazzoleni Calogero Maria Oddo Mariangela Filosa Department of Electrical and Information Engineering Polytechnic University of Bari Italy Department of Excellence in Robotics & AI The BioRobotics Institute Sant' Anna School of Advanced Studies Pisa Italy Interdisciplinary Research Center Health Science Sant’ Anna School of Advanced Studies Pisa Italy

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

The field of collaborative robotics is constantly growing given the central role that safe human-robot interactions are gaining in the current era of Industry 4.0. To act and interact, robotic systems are increasingly being either natively equipped with or adapted to house sensing devices. In this scenario, tactile sensors are fundamental to detect impacts, accurately manipulate objects and enable learning from demonstration strategies. The development of such systems requires technological efforts in terms of both design, for their seamless integration in robots, and software programming, for achieving reliable and prompt reactions to relevant events. In this study, an edge ai algorithm deployed on an embedded device for the recognition of contacts on an FBG (Fiber Bragg Grating)-based e-skin is presented. A Convolutional Neural Network has been trained offline to localize touch events occurred on the e-skin. The performance of the algorithm assessed on the test set reached a mean absolute error on the three cartesian coordinates of less than 4 mm. The algorithm has been then ported to a microcontroller board for real-time testing of both simulated and concurrent contacts. The achievements of this work pave the way to new opportunities for collaborative robotics applications through intelligent FBG-based artificial tactile skins.

关键词： Service robots Robot kinematics Software algorithms Tactile sensors Collaboration Edge ai Fiber gratings Software Software reliability Testing

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DESectBot: Design and Validation of a Novel Two-Segment Decoupled Continuum Robotic System for Endoscopic Submucosal Dissection

DESectBot: Design and Validation of a Novel Two-Segment Deco...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Wenjie Liu Yuancheng Shao Yao Zhang Zixi Chen Di Wu Yuqiao Chen Cesare Stefanini Ling Li Peng Qi Department of Control Science and Engineering Tongji University Shanghai China Zhuhai Institute of Advanced Technology Zhuhai China Department of Mechanical Engineering KU Leuven Belgium Department of Excellence in Robotics and AI Biorobotics Institute Pisa Italy Suzhou Ultimage Health Technology Co. Ltd. Suzhou China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Endoscopic Submucosal Dissection (ESD) is a minimally invasive procedure designed to remove precancerous and cancerous lesions from the gastrointestinal (GI) tract. Given the GI tract’s tortuous and narrow shape, along with the need for varied movements during dissection, this requires highly flexible and compact instruments, making flexible continuum robots suitable candidates. In this paper, we propose a novel two-segment continuum robot system named DESectBot, featuring a diameter of 5.5 mm and a total length of the active bending module of 48 mm, while the robot’s total length exceeds 1 m. We designed a novel joint combination structure called the spatial cross-curved disk skeleton for the robot, which addresses the mechanical coupling problem between flexible robot actuators. The DESectBot boasts six degrees of freedom, and its kinematic modeling has been derived and utilized in the closed-loop control of the DESectBot. The validation of the DESectBot was conducted through a two-stage test: first, the decoupling performance of the DESectBot was validated. The results show that when one active bending segment bends, the other segment remains almost uninfluenced, with a maximum variation of 1.15 degrees, demonstrating the robot’s effective decoupling capability. Secondly, the accuracy of DESectBot was validated through trajectory-following experiments. The results reveal that the average tracking error for both trajectories is less than 2 mm, and the maximum tracking error is below 2.5 mm. Taking marking, one of the ESD procedures with a 5mm tolerance, as an example, the DESectBot has the potential to be utilized for ESD procedure.

关键词： Minimally invasive surgery Shape Kinematics Bending Electrostatic discharges Skeleton Trajectory Continuum robots Lesions Intelligent robots

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A Sine Wave-Shaped Spring to Enhance the Compactness of Series Elastic Actuators

A Sine Wave-Shaped Spring to Enhance the Compactness of Seri...

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International Conference on Advanced robotics (ICAR)

作者： Marcello Palagi Gianluca Rinaldi Giancarlo Santamato Massimiliano Solazzi Antonio Frisoli Domenico Chiaradia Department of Excellence in Robotics & AI Institute of Mechanical Intelligence Scuola Superiore Sant'Anna Pisa Italy

In this paper, we discuss the design methodology of a novel torsional spring, embedded in a series elastic actuator (SEA) for portable upper-limb exoskeleton applications. Starting from a simple beam model, a class of design candidates is examined through theoretical formulation and finite element (FE) simulations. We found out that a sine wave shape is the best compromise to achieve the desired compliance for a safe use of the exos. Besides, this novel design reveals to reduce the encumbrance of the joint with respect to previous architectures, for fixed weight. The spring was manufactured in a 3D-printed metal with main dimensions - $\phi$ diameter 98 mm, 18 mm of width - and weight - 0.34 kg. Experiments have been performed on the SEA to validate the joint characteristic in the torque-angle plane. Results are promising since linearity is confirmed and the experimental stiffness coincides with the theoretical estimate. In particular, the joint is validated for operation up to a deflection of 13.75° under a nominal torque of 9 Nm. Therefore, the proposed elastic joint is suitable for integration in physical human-robot interactions.

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Modeling, Optimization, and Musculoskeletal Simulation of Elbow-Wrist Exosuit

Modeling, Optimization, and Musculoskeletal Simulation of El...

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International Conference on Advanced robotics (ICAR)

作者： Ali KhalilianMotamed Bonab Daniele Leonardis Antonio Frisoli Domenico Chiaradia Department of Excellence in Robotics & AI Scuola Superiore Sant'Anna Institute of Mechanical Intelligence Pisa Italy

Exosuits present intriguing structural advantages compared to exoskeletons; nevertheless, accurately modeling and simulating their effectiveness when integrated with the musculoskeletal system of the user poses formidable challenges. As regards the upper limb, there are limited approaches and models in the literature that consider both the complexities of the musculoskeletal system and the optimization of the exosuit interface. In this work, we propose an extensive approach that considers both a mathematical model of a wrist-elbow exosuit, and simulations of a complex upper limb musculoskeletal system. The kinematic and dynamic model of the exosuit allows for the optimization of the anchor points, while the simulation provides information on muscular loading with and without assistance. In the presented results we have developed and validated personalized musculoskeletal models with kinematic, anthropometric, and electromyographic data we measured in a load-lifting task. The results of the simulations show the effectiveness of the optimized exosuit and reveal the impact of the exosuit at the level of the whole upper limb, and not limited to the actuated districts only.

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Continuous Gait Phase Estimation and Torque Profile Generation Using Adaptive Dynamic Movement Primitives for Able-Bodied Individuals and Stroke Survivors

Continuous Gait Phase Estimation and Torque Profile Generati...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Huseyin Eken Chiara Livolsi Andrea Pergolini Michele Francesco Penna Giovanni Hamoui Emanuele Gruppioni Emilio Trigili Simona Crea Nicola Vitiello BioRobotics Institute Scuola Superiore Sant’ Anna Pontedera Italy Department of Excellence in Robotics & AI Scuola Superiore Sant'Anna Pisa Italy Centro Protesi Inail di Vigorso di Budrio Bologna Italy Università di Bologna Bologna Italy

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Continuous gait phase estimation facilitates the real-time synchronization of wearable robotic assistive strategies with the user's movements, ensuring seamless operation across varying walking speeds. A previous study showed that adaptive Dynamic Movement Primitives (aDMP) can estimate the gait phase in real time for various locomotion activities of daily life. Advancing this paradigm, this study has two objectives. Firstly, it investigates the use of aDMP-based gait phase estimation to generate phase-dependent torque profiles using a powered unilateral hip exoskeleton. Tests were conducted with six able-bodied participants in level-ground walking. In these tests, the performance of the aDMP algorithm was assessed using subject-dependent and subject-independent models. Secondly, this study investigates the applicability of aDMP to estimate the gait phase for a pathological gait, using a dataset from six stroke survivors. Results with able-bodied participants demonstrated that root mean square errors (RMSE) in phase estimation were between 2.75-5% relative to the linear phase across all experimental conditions, including assistive and transparent (i.e., zero-torque) modes with subject-dependent and subject-independent models. Results with stroke survivors exhibited a median RMSE of 6.75 % when the exoskeleton was operated in transparent mode. These results demonstrated that aDMP-based gait phase estimation can effectively generate phase-locked torque profiles for able-bodied participants. However, further research is needed to validate these findings in stroke survivors, as the preliminary offline results indicated a higher RMSE in this population.

关键词： Legged locomotion Pathology Torque Phase estimation Exoskeletons Real-time systems Synchronization Root mean square Robots Hip

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Towards Interpretable Visuo-Tactile Predictive Models for Soft Robot Interactions

arXiv

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arXiv 2024年

作者： Donato, Enrico Thuruthel, Thomas George Falotico, Egidio The BioRobotics Institute Sant’Anna School of Advanced Studies PI Pontedera56025 Italy The Departement of Excellence in Robotics & AI Sant’Anna School of Advanced Studies Pisa56125 Italy The Department of Computer Science University College London London United Kingdom

Autonomous systems face the intricate challenge of navigating unpredictable environments and interacting with external objects. The successful integration of robotic agents into real-world situations hinges on their perception capabilities, which involve amalgamating world models and predictive skills. Effective perception models build upon the fusion of various sensory modalities to probe the surroundings. Deep learning applied to raw sensory modalities offers a viable option. However, learning-based perceptive representations become difficult to interpret. This challenge is particularly pronounced in soft robots, where the compliance of structures and materials makes prediction even harder. Our work addresses this complexity by harnessing a generative model to construct a multi-modal perception model for soft robots and to leverage proprioceptive and visual information to anticipate and interpret contact interactions with external objects. A suite of tools to interpret the perception model is furnished, shedding light on the fusion and prediction processes across multiple sensory inputs after the learning phase. We will delve into the outlooks of the perception model and its implications for control purposes. © 2024, CC BY-NC-ND.

关键词： Deep learning

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Multi-modal perception for soft robotic interactions using generative models

arXiv

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arXiv 2024年

作者： Donato, Enrico Falotico, Egidio Thuruthel, Thomas George The BioRobotics Institute Sant’Anna School of Advanced Studies PI Pontedera56025 Italy The Departement of Excellence in Robotics & AI Sant’Anna School of Advanced Studies Pisa56125 Italy The Department of Computer Science University College London London United Kingdom

Perception is essential for the active interaction of physical agents with the external environment. The integration of multiple sensory modalities, such as touch and vision, enhances this perceptual process, creating a more comprehensive and robust understanding of the world. Such fusion is particularly useful for highly deformable bodies such as soft robots. Developing a compact, yet comprehensive state representation from multi-sensory inputs can pave the way for the development of complex control strategies. This paper introduces a perception model that harmonizes data from diverse modalities to build a holistic state representation and assimilate essential information. The model relies on the causality between sensory input and robotic actions, employing a generative model to efficiently compress fused information and predict the next observation. We present, for the first time, a study on how touch can be predicted from vision and proprioception on soft robots, the importance of the cross-modal generation and why this is essential for soft robotic interactions in unstructured environments. © 2024, CC BY-NC-ND.

关键词： Robot vision

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Plant-inspired behavior-based controller to enable reaching in redundant continuum robot arms

Plant-inspired behavior-based controller to enable reaching ...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Enrico Donato Yasmin Tauqeer Ansari Cecilia Laschi Egidio Falotico The BioRobotics Institute Sant'Anna School of Advanced Studies Pontedera PI Italy Departement of Excellence in Robotics ' AI Sant'Anna School of Advanced Studies Pisa Italy Department of Mechanical Engineering National University of Singapore Singapore BioRobotics Institute Sant'Anna School of Advanced Studies Pisa Italy

Enabling reaching capabilities in highly redundant continuum robot arms is an active area of research. Existing solutions comprise of task-space controllers, whose proper functioning is still limited to laboratory environments. In contrast, this work proposes a novel plant-inspired behaviour-based controller that exploits information obtained from proximity sensing embedded near the end-effector to move towards a desired spatial target. The controller is tested on a 9-DoF modular cable-driven continuum arm for reaching multiple set-points in space. The results are promising for the deployability of these systems into unstructured environments.

关键词： Laboratories Soft robotics Aerospace electronics Robot sensing systems End effectors Sensors Behavioral sciences

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