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Development and Functional Evaluation of The PrHand V3 Soft-robotics Prosthetic Hand

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Development and Functional Evaluation of The PrHand V3 Soft-...

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

作者： Orion Ramos Laura De Arco Marcela Múnera Jorge Robledo Mehran Moazen Helge Wurdemann Carlos A. Cifuentes School of Engineering Science and Technology Universidad del Rosario Bogota Colombia Graduate Program of Electrical Engineering Federal University of Espírito Santo Vitoria Brazil Bristol Robotics Laboratory University of the West of England Bristol UK Colombian School of Engineering Bogotá D.C. Colombia Prótesis Avanzadas SAS Medellin Colombia Department of Mechanical Engineering University College London London UK

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

The affordability and functionality of hand prosthetics in developing countries are still very limited. This work aims to present and evaluate the new version of the PrHand affordable robotic prosthesis (PrHand V3), built with soft robotics and compliant mechanisms. PrHand V3 implements a new frictionless tendon unification system, the degree of freedom of thumb opposition was removed, and the finger flexion was improved to the previous version, PrHand V2. The study contributes by evaluating these mechanical changes and conducting the first functional assessment of PrHand V3 with an amputee user. The Anthropomorphic Hand Assessment Protocol (AHAP) dexterity test was the first evaluation in this work; it evaluated how the prosthesis performs eight different grips. PrHand V3 was compared with a PrHand V2 and a commercial robotic prosthesis A3D from Prótesis Avanzadas SAS. PrHand V3’s score on the AHAP test was 80%. This result is higher than the 69% obtained by the PrHand V2 and the 79% obtained by A3D. The Activities Measure for Upper Limb Amputees (AM-ULA) test was the second evaluation in this work; An A3D amputee user performed 23 Activities of Daily Living with PrHand V3 and an A3D. PrHand V3 obtained an average of 2.86/4 and A3D obtained an average of 2.96/4 without significant differences between the two tests. The soft actuation of PrHand V3 as an affordable prosthesis performs similarly to a commercial robotic prosthesis with the advantage of being more flexible to assist a trans-radial hand amputee.

关键词： Hands Protocols Manufacturing processes Thumb Grasping Soft robotics Synthetic aperture sonar Prosthetic hand Prosthetics Tendons

Row-wise LiDAR Lane Detection Network with Lane Correlation Refinement

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arXiv 2022年

作者： Paek, Dong-Hee Wijaya, Kevin Tirta Kong, Seung-Hyun The CCS Graduate School of Mobility Korea Advanced Institute of Science and Technology 193 Munji-ro Yuseong-gu Daejeon Korea Republic of The Robotics Program Korea Advanced Institute of Science and Technology 291 Daehak-ro Yuseong-gu Daejeon Korea Republic of

Lane detection is one of the most important functions for autonomous driving. In recent years, deep learning-based lane detection networks with RGB camera images have shown promising performance. However, camera-based methods are inherently vulnerable to adverse lighting conditions such as poor or dazzling lighting. Unlike camera, LiDAR sensor is robust to the lighting conditions. In this work, we propose a novel two-stage LiDAR lane detection network with row-wise detection approach. The first-stage network produces lane proposals through a global feature correlator backbone and a row-wise detection head. Meanwhile, the second-stage network refines the feature map of the first-stage network via attention-based mechanism between the local features around the lane proposals, and outputs a set of new lane proposals. Experimental results on the K-Lane dataset show that the proposed network advances the state-of-the-art in terms of F1-score with 30% less GFLOPs. In addition, the second-stage network is found to be especially robust to lane occlusions, thus, demonstrating the robustness of the proposed network for driving in crowded environments. Copyright © 2022, The Authors. All rights reserved.

关键词： Cameras

DeepCat: A Deep Learning Approach to Understand Your Cat's Body Language

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DeepCat: A Deep Learning Approach to Understand Your Cat's B...

Electronics, Communications, and Computations (JAC-ECC), International Japan-Africa Conference on

作者： Arwa Fawzy Ahmed Hassan Ahmed Gad Ahmed B. Zaky Haitham El-Hussieny Computer Science and Information Technology (CSIT) program Egypt-Japan University of Science and Technology Alexandria Egypt Department of Computer Science Engineering (CSE) Egypt-Japan University of Science and Technology Alexandria Egypt Electrical Engineering Department Faculty of Engineering at Shoubra Benha University Egypt Department of Mechatronics and Robotics Engineering Egypt-Japan University of Science and Technology Alexandria Egypt

Pet owners experience difficulty in understanding their pets' body language and its implications for animal welfare, given that animals cannot utilize human speech to communicate their emotions and health conditions. However, previous experiments for analyzing cat behavior have demonstrated that cats are precisely expressive. DeepCat, a deep-learning approach developed in this study, translates cats' body language signals, enabling owners to discern their feline companions' intended messages and emotional states. Our DeepCat model was trained on a dataset comprising 10,000 cat images, implementing automatic labeling to track key features, including the tail, eyes, and mouth. Presented as a Flutter application, DeepCat can function everywhere, allowing owners to easily monitor their cats and make informed decisions in situations that require caution. This paper discusses the potential benefits and limitations of DeepCat and provides suggestions for future research in this domain.

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The test evaluation and analysis of input-voltage variation of DC/AC inverter in auxiliary power supply of electric propulsion ship

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Transactions of the Korean Institute of Electrical Engineers 2020年第8期69卷 1216-1220页

作者： Song, Wang-Keun Choi, Yong-Hoon Division of Robotics Kwangwoon University Korea Republic of Defense Acquisition Program Kwangwoon University Korea Republic of

The main power supply of electric vehicles and ships is generally composed of a battery, a generator and a fuel cell, and a propulsion motor and inverter are used as a driving device. In addition to the main power supply for electric power-driven driving, additional auxiliary power supply for control system and auxiliary system is required, and power conversion devices (inverters and converters) are used for this purpose. Power conversion devices for auxiliary power supply receives power from main power supply such as battery, generator and fuel cell and performs the AC or DC power conversion. The voltage variation of main power supply depends on the usage conditions of electric propulsion system. The power conversion devices for auxiliary power supply shall not cause output stop even if the voltage of main power supply suddenly changes to the allowable voltage range. The output of the power conversion devices for auxiliary power supply shall have an operating capability to produce a stable output within the permitted voltage range. This paper deals with the test evaluation and analysis for the input voltage fluctuation of the DC/AC inverter(power conversion devices) in auxiliary power supply of electric ship.. © 2020 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Electric vehicles

Variable Stiffness Hip Joint for Lower-Limb Exoskeletons

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Variable Stiffness Hip Joint for Lower-Limb Exoskeletons

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

作者： Sophia Otálora Hector A. Moreno Marcela Múnera Carlos A. Cifuentes Graduate Program of Electrical Engineering Federal University of Espirito Santo Vitoria Brazil Facultad de Ingeniería Mecánica y Eléctrica Universidad Autónoma de Coahuila Av. Barranquilla s/n Col. Guadalupe Monclova Coah. Mexico Bristol Robotics Laboratory University of the West of England Bristol UK Department of Biomedical Engineering Colombian School of Engineering Julio Garavito Bogota Colombia

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

The use of robotics in rehabilitation is a growing area of research, with the potential to greatly improve the quality of life for individuals with impairments. Robotic exoskeletons, in particular, have shown promise for enhancing mobility and independence in patients with conditions such as stroke. Current exoskeleton designs, however, often lack the necessary degrees of freedom (DOFs) to provide adequate balance and support during activities of daily living (ADLs), such as walking and standing. This study proposes a new lower limb exoskeleton design incorporating a variable stiffness hip joint based on a four-bar mechanism. This joint provides additional DOFs for improved balance and stability during gait, making it easier for patients to perform ADLs. The results show that the exoskeleton effectively improves stability during gait testing. This suggests that the proposed design can greatly enhance mobility and independence in impaired patients and could be a valuable tool in rehabilitation robotics.

关键词： Legged locomotion Exoskeletons Biomechatronics Stroke (medical condition) Assistive robots Robots Hip Testing

Game-theoretic model predictive control with data-driven identification of vehicle model for head-to-head autonomous racing

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arXiv 2021年

作者： Jung, Chanyoung Lee, Seungwook Seong, Hyunki Finazzi, Andrea Shim, David Hyunchul School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of KAIST Robotics Program Korea Advanced Institute of Science and Technology Daejeon Korea Republic of

Resolving edge-cases in autonomous driving, head-to-head autonomous racing is getting a lot of attention from the industry and academia. In this study, we propose a game-theoretic model predictive control (MPC) approach for head-to-head autonomous racing and data-driven model identification method. For the practical estimation of nonlinear model parameters, we adopted the hyperband algorithm, which is used for neural model training in machine learning. The proposed controller comprises three modules: 1) game-based opponents’ trajectory predictor, 2) high-level race strategy planner, and 3) MPC-based low-level controller. The game-based predictor was designed to predict the future trajectories of competitors. Based on the prediction results, the high-level race strategy planner plans several behaviors to respond to various race circumstances. Finally, the MPC-based controller computes the optimal control commands to follow the trajectories. The proposed approach was validated under various racing circumstances in an official simulator of the Indy Autonomous Challenge. The experimental results show that the proposed method can effectively overtake competitors, while driving through the track as quickly as possible without collisions. © 2021, CC BY-NC-SA.

关键词： Model predictive control

ThinkCarpet: Potentializing Computational Thinking with Educational robotics in Middle School

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ThinkCarpet: Potentializing Computational Thinking with Educ...

IEEE Latin American robotics Symposium, LARS

作者： Almir De Oliveira Costa Junior João Paulo Felizardo Lima e Silva José Anglada Rivera Elloá B. Guedes Post-Graduate Program in Technological Teaching Amazonas Federal Institute (IFAM) Manaus Amazonas Brazil Research Group on Educational Robotics Amazonas State University (UEA) Manaus Amazonas Brazil Research Group on Intelligent Systems Amazonas State University (UEA) Manaus Amazonas Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

ThinkCarpet is an interactive Educational robotics artifact built using alternative materials and Arduino. It aims at assisting Middle School students in the development of Computational Thinking with plugged activities for learning about algorithms. In this context, this work presents the results of a usability evaluation of ThinkCarpet with a medium fidelity prototype. The assessment was based on the use of the System Usability Scale and was carried out with 16 students from the 6 th Grade of Middle School. Results show a SUS Score of 83.59 which classifies ThinkCarpet as excellent in a realistic scenario.

关键词： Conferences Education Prototypes Usability Robots

PoseViNet: Distracted Driver Action Recognition Framework Using Multi-View Pose Estimation and Vision Transformer

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arXiv 2023年

作者： Sengar, Neha Kumari, Indra Lee, Jihui Har, Dongsoo The Robotics Program Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Korea Institute of Science and Technology Information Daejeon34141 Korea Republic of The Division of Future Vehicle Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of The CCS Graduate School of Green Transportation Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of

Driver distraction is a principal cause of traffic accidents. In a study conducted by the National Highway Traffic Safety Administration, engaging in activities such as interacting with in-car menus, consuming food or beverages, or engaging in telephonic conversations while operating a vehicle can be significant sources of driver distraction. From this viewpoint, this paper introduces a novel method for detection of driver distraction using multi-view driver action images. The proposed method is a vision transformer-based framework with pose estimation and action inference, namely PoseViNet. The motivation for adding posture information is to enable the transformer to focus more on key features. As a result, the framework is more adept at identifying critical actions. The proposed framework is compared with various state-of-the-art models using SFD3 dataset representing 10 behaviors of drivers. It is found from the comparison that the PoseViNet outperforms these models. The proposed framework is also evaluated with the SynDD1 dataset representing 16 behaviors of driver. As a result, the PoseViNet achieves 97.55% validation accuracy and 90.92% testing accuracy with the challenging dataset. © 2023, CC BY.

关键词： Deep learning

Dynamic hypergames for synthesis of deceptive strategies with temporal logic objectives

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arXiv 2020年

作者： Li, Lening Ma, Haoxiang Kulkarni, Abhishek N. Fu, Jie Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States Faculty of Electrical and Computer Engineering Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States

In this paper, we study the use of deception for strategic planning in adversarial environments. We model the interaction between the agent (player 1) and the adversary (player 2) as a two-player concurrent game in which the adversary has incomplete information about the agent’s task specification in temporal logic. During the online interaction, the adversary can infer the agent’s intention from observations and adapt its strategy so as to prevent the agent from satisfying the task. To plan against such an adaptive opponent, the agent must leverage its knowledge about the adversary’s incomplete information to influence the behavior of the opponent, and thereby being deceptive. To synthesize a deceptive strategy, we introduce a class of hypergame models that capture the interaction between the agent and its adversary given asymmetric, incomplete information. A hypergame is a hierarchy of games, perceived differently by the agent and its adversary. We develop the solution concept of this class of hypergames and show that the subjectively rationalizable strategy for the agent is deceptive and maximizes the probability of satisfying the task in temporal logic. This deceptive strategy is obtained by modeling the opponent evolving perception of the interaction and integrating the opponent model into proactive planning. Following the deceptive strategy, the agent chooses actions to influence the game history as well as to manipulate the adversary’s perception so that it takes actions that benefit the goal of the agent. We demonstrate the correctness of our deceptive planning algorithm using robot motion planning examples with temporal logic objectives and design a detection mechanism to notify the agent of potential errors in modeling of the adversary’s behavior. Copyright © 2020, The Authors. All rights reserved.

关键词： Markov processes