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CoNECD 2021

作者： Kenemuth, Rebecca Z. Nguyen, Vincent Sabihi, Sama Women in Engineering Program The University of Maryland United States University of Maryland Department of Mechanical Engineering United States

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Modeling Actuation of Ionomer Cilia in Salt Solution under an External Electric Field

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ASME Letters in Dynamic Systems and Control 2021年第1期1卷 011006页

作者： Boldini, Alain Rosen, Maxwell Cha, Youngsu Porfiri, Maurizio Department of Mechanical and Aeronautical Engineering New York University Tandon School of Engineering BrooklynNY11201 United States Center for Intelligent and Interactive Robotics Korea Institute of Science and Technology Seoul02792 Korea Republic of

A recent experiment by Kim's group from the University of Nevada, Las Vegas, has shown the possibility of actuating ionomer cilia in salt solution. When these actuators are placed between two external electrodes, across which a small voltage is applied, they move toward the cathode. This is in stark contrast with ionic polymer metal composites, where the same ionomers are plated by metal electrodes but bending occurs toward the anode. Here, we seek to unravel the factors underlying the motion of ionomer cilia in salt solution through a physically based model of actuation. In our model, electrochemistry is described through the Poisson-Nernst-Planck system in terms of concentrations of cations and anions and voltage. Through finite element analysis, we establish that Maxwell stress is the main driving force for the motion of the cilia. This study constitutes a first effort toward understanding the motion of ionomer cilia in salt solution, which, in turn, may help elucidate the physical underpinnings of actuation in ionic polymer metal composites. © 2021 ASME Letters in Dynamic Systems and Control. All rights reserved.

关键词： Electrochemistry

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An Actor-Critic Reinforcement Learning Scheme for Reactive 3D Optimal Motion Planning Based on Fluid Dynamics

An Actor-Critic Reinforcement Learning Scheme for Reactive 3...

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

作者： Marios Malliaropoulos Panagiotis Rousseas Charalampos P. Bechlioulis Kostas J. Kyriakopoulos School of Mechanical Engineering Control Systems Laboratory National Technical University of Athens Department of Electrical and Computer Engineering University of Patras Center of AI & Robotics (CAIR) New York University Abu Dhabi

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This work proposes a novel and provably correct method for three-dimensional optimal motion planning in complex environments. Our approach models the 3D motion planning problem by solving streamlines of the potential fluid flow, filling a gap in traditional motion planning techniques by guaranteeing a closed-loop, smooth and natural-looking navigation solution. Special emphasis is given to an inherent challenge of artificial potential field (APF) methods, namely establishing proofs of safety and stability over the entire optimization process. A model-based actor-critic reinforcement learning algorithm is introduced to approximate the optimal solution to the Hamilton-Jacobi-Bellman equation and update the controller parameters in a deterministic manner. Through a series of ROS-Gazebo software-in-the-loop simulations the proposed methodology demonstrates robustness and outperforms widely used methods such as the RRT ∗ , highlighting its contribution to the field of 3D optimal motion planning.

关键词： Solid modeling Three-dimensional displays Navigation Reinforcement learning Mathematical models Stability analysis Robustness Planning Safety Optimization

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Active Exploration for Real-Time Haptic Training

Active Exploration for Real-Time Haptic Training

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jake Ketchum Ahalya Prabhakar Todd D. Murphey Center for Robotics and Biosystems Northwestern University Evanston IL USA Department of Mechanical Engineering and Materials Science Yale University New Haven CT USA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Tactile perception is important for robotic systems that interact with the world through touch. Touch is an active sense in which tactile measurements depend on the contact properties of an interaction—e.g., velocity, force, acceleration— as well as properties of the sensor and object under test. These dependencies make training tactile perceptual models challenging. Additionally, the effects of limited sensor life and the near-field nature of tactile sensors preclude the practical collection of exhaustive data sets even for fairly simple objects. Active learning provides a mechanism for focusing on only the most informative aspects of an object during data collection. Here we employ an active learning approach that uses a data-driven model’s entropy as an uncertainty measure and explore relative to that entropy conditioned on the sensor state variables. Using a coverage-based ergodic controller, we train perceptual models in near-real time. We demonstrate our approach using a biomimentic sensor, exploring "tactile scenes" composed of shapes, textures, and objects. Each learned representation provides a perceptual sensor model for a particular tactile scene. Models trained on actively collected data outperform their randomly collected counterparts in real-time training tests. Additionally, we find that the resulting network entropy maps can be used to identify high salience portions of a tactile scene.

关键词： Training Uncertainty Biological system modeling Tactile sensors Entropy Real-time systems Haptic interfaces

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TartanDrive 2.0: More Modalities and Better Infrastructure to Further Self-Supervised Learning Research in Off-Road Driving Tasks

arXiv

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arXiv 2024年

作者： Sivaprakasam, Matthew Maheshwari, Parv Castro, Mateo Guaman Triest, Samuel Nye, Micah Willits, Steve Saba, Andrew Wang, Wenshan Scherer, Sebastian Robotics Institute Carnegie Mellon University United States Department of Mathematics Indian Institute of Technology Kharagpur India Department of Mechanical Engineering University of Pittsburgh United States

We present TartanDrive 2.0, a large-scale off-road driving dataset for self-supervised learning tasks. In 2021 we released TartanDrive 1.0, which is one of the largest datasets for off-road terrain. As a follow-up to our original dataset, we collected seven hours of data at speeds of up to 15m/s with the addition of three new LiDAR sensors alongside the original camera, inertial, GPS, and proprioceptive sensors. We also release the tools we use for collecting, processing, and querying the data, including our metadata system designed to further the utility of our data. Custom infrastructure allows end users to reconfigure the data to cater to their own platforms. These tools and infrastructure alongside the dataset are useful for a variety of tasks in the field of off-road autonomy and, by releasing them, we encourage collaborative data aggregation. These resources lower the barrier to entry to utilizing large-scale datasets, thereby helping facilitate the advancement of robotics in areas such as self-supervised learning, multi-modal perception, inverse reinforcement learning, and representation learning. The dataset is available at https://***/TartanDrive2. © 2024, CC BY.

关键词： Large datasets

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Quantifying Joint Movement Variability in Healthy and Hemiplegic Gait using OpenSim

Quantifying Joint Movement Variability in Healthy and Hemipl...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Tabassum Rafiq Sadia Younis Jyotindra Narayan Department of Biotechnology Institute of Information Management and Technology Aligarh Uttar Pradesh India Department of Biomedical Engineering Government College of Engineering and Technology Ganderbal Jammu and Kashmir India Department of Mechanical Engineering Mechatronics and Robotics Laboratory Indian Institute of Technology Guwahati Guwahati Assam India

This study delves into the scaling capabilities of OpenSim, a biomechanical modeling tool, to scrutinize musculoskeletal alterations accompanying the hemiplegic condition compared to a healthy model. Contralateral hemiplegia (CH), characterized by unilateral paralysis, induces profound changes in bone size and significantly influences an individual’s gait. Motivated by understanding the biomechanical repercussions of CH on human movement, we conducted a comprehensive investigation involving ten patients with CH, with a median age of 46 years (range: 39 to 52.0 years and height: 1.75 0.6 m). Ten healthy controls with similar body attributes were±also recruited. We assessed musculoskeletal changes post-CH using bone length data from MRI reports obtained from a hospital. Inverse kinematics in OpenSim are facilitated for a detailed comparison of joint angles between unhealthy and healthy individuals. The gait data is visualized and analyzed using statistical metrics such as mean absolute deviation, box plots, and a two-sample t-test. The results revealed significant differences in hip and ankle joint angles between healthy and hemiplegic individuals, underscored by low p-values. Interestingly, no significant difference was observed in knee joint angles (p-value = 0.9126). These findings contribute to a valuable understanding of hemiplegia-related musculoskeletal changes, offering potential avenues for tailored interventions to improve mobility and quality of life.

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Soft Fluidic Closed-Loop Controller for Untethered Underwater Gliders

Soft Fluidic Closed-Loop Controller for Untethered Underwate...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Kalina Bonofiglio Lauryn Whiteside Maya Angeles Matthew Haahr Brandon Simpson Josh Palmer Yijia Wu Markus P. Nemitz Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA Department of Mechanical Engineering Worcester Polytechnic Institute Worcester MA USA Department of Electrical Engineering Worcester Polytechnic Institute Worcester MA USA

Soft underwater robots typically explore bio-inspired designs at the expense of power efficiency when compared to traditional underwater robots, which limits their practical use in real-world applications. We leverage a fluidic closed-loop controller to actuate a passive underwater glider. A soft hydrostatic pressure sensor is configured as a bang-bang controller actuating a swim bladder made from silicone balloons. Our underwater glider oscillates between the water surface and 4 m depth while traveling 15 m translationally. The fluidic underwater glider demonstrates a power efficiency of 28 mW/m. This work demonstrates a low-cost and power-efficient underwater glider and non-electronic controller. Due to its simple design, low cost, and ease of fabrication using FDM printing and soft lithography, it serves as a starting point for the exploration of non-electronic underwater soft robots.

关键词： Fabrication Pressure sensors Autonomous underwater vehicles Soft lithography Power demand Costs Soft robotics

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Predictive Simulation of Hemiparetic Gait Based on Neural Impairments

Predictive Simulation of Hemiparetic Gait Based on Neural Im...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Hossein Barati Kamran Nazari Iman Kardan Alireza Akbarzadeh Department of Mechanical Engineering Center of Advanced Rehabilitation and Robotics Research (FUM-CARE) Ferdowsi University of Mashhad Mashhad Iran

Hemiparetic gait is the most common walking impairment after a stroke that causes abnormal movement patterns. However, the neuromuscular impairments that may lead to this type of gait are not fully understood. Predictive neuromechanical simulations allow for exploring how neural and biomechanical impairments affect gait performance based on dynamic optimization method. To simulate a hemiparetic gait, we used a predictive simulation software (SCONE) with a neuromuscular model of human, walking in the sagittal plane. The model is used to implement different neural impairments such as decreased unilateral muscle excitations and spastic hyperreflexia in quadriceps and ankle plantar flexors. Neural impairments were modeled in three cases of pure neural weakness, pure spastic hyperreflexia, and a combination of both, to investigate their contribution to hemiparetic gait. For validation, all simulation results were compared with experimental gait data of hemiparetic stroke patients. Our results exhibited better agreement with experimental data when a combination of neural impairments was used to simulate hemiparetic gait. In this case, the walking speed was slower than in other cases (0.47 m/s), and spatiotemporal parameters matched well with experimental data. The cross-correlation was highest in paretic knee angle $(\mathrm{R}=0.99)$ and strong in paretic and non-paretic hip angle $(\mathrm{R}\gt 0.92)$. In terms of joint kinetics, hip and ankle moments showed strong cross-correlation in the paretic side $(\mathrm{R}\gt 0.71)$ and moderate in knee moment $(\mathrm{R}=0.66)$. Future works could utilize our predictive simulations to design and develop assistive devices and control strategies of lower-limb exoskeletons to improve gait performance in post-stroke patients.

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Merging in a Coupled Driving Simulator: How do drivers resolve conflicts?

arXiv

引用

arXiv 2023年

作者： Siebinga, Olger Zgonnikov, Arkady Abbink, David A. Human-Robot Interaction Group Department of Cognitive Robotics Faculty of Mechanical Engineering Delft University of Technology Delft Netherlands

Traffic interactions between merging and highway vehicles are a major topic of research, yielding many empirical studies and models of driver behaviour. Most of these studies on merging use naturalistic data. Although this provides insight into human gap acceptance and traffic flow effects, it obscures the operational inputs of interacting drivers. Besides that, researchers have no control over the vehicle kinematics (i.e., positions and velocities) at the start of the interactions. Therefore the relationship between initial kinematics and the outcome of the interaction is difficult to investigate. To address these gaps, we conducted an experiment in a coupled driving simulator with a simplified, top-down view, merging scenario with two vehicles. We found that kinematics can explain the outcome (i.e., which driver merges first) and the duration of the merging conflict. Furthermore, our results show that drivers use key decision moments combined with constant acceleration inputs (intermittent piecewise-constant control) during merging. This indicates that they do not continuously optimize their expected utility. Therefore, these results advocate the development of interaction models based on intermittent piecewise-constant control. We hope our work can contribute to this development and to the fundamental knowledge of interactive driver behaviour. © 2023, CC BY.

关键词： Merging

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Improving Sit/Stand Loading Symmetry and Timing Through Unified Variable Impedance Control of a Powered Knee-Ankle Prosthesis

TechRxiv

引用

TechRxiv 2024年

作者： Welker, Cara Gonzalez Best, T. Kevin Gregg, Robert D. Department of Mechanical Engineering University of Colorado Boulder BoulderCO80309 United States Department of Robotics University of Michigan Ann ArborMI48109 United States

Individuals using passive prostheses typically rely heavily on their biological limb to complete sitting and standing tasks, leading to slower completion times and increased rates of osteoarthritis and lower back pain. Powered prostheses can address these challenges, but have control methods that divide sit-stand transitions into discrete phases, limiting user synchronization across the motion and requiring long manual tuning times. This paper extends our preliminary work using a thigh-based phase variable to parameterize optimized data-driven impedance parameter trajectories for sitting, standing, and walking, with only two classification modes. We decouple the stand-to-sit and sit-to-stand equilibrium angles through a knee velocity-dependent scaling term, reducing the model fitting error by approximately half compared to our previous results. We then experimentally validate the controller with three individuals with above-knee amputation performing sitting and standing transitions to/from three different chair heights. We show that our controller implemented on a powered knee-ankle prosthesis produced biomimetic joint mechanics, resulting in significantly reduced sit/stand loading asymmetry and time to complete a 5x sit-to-stand task compared to participants’ passive prostheses. Integration with a previously developed walking controller also allowed sit/walk transitions between different chair heights. The controller’s biomimetic assistance may reduce the overreliance on the biological limb caused by inadequate passive prostheses, helping improve mobility for people with above-knee amputations. © 2024, CC BY-NC-SA.

关键词： Knee prostheses

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