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arXiv 2023年

作者： Zhong, Fangxun Liu, Yun-Hui T Stone Robotics Institute Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

Agile maneuvers are essential for robot-enabled complex tasks such as surgical procedures. Prior explorations on surgery autonomy are limited to feasibility study of completing a single task without systematically addressing generic manipulation safety across different tasks. We present an integrated planning and control framework for 6-DoF robotic instruments for pipeline automation of surgical tasks. We leverage the geometry of a robotic instrument and propose the nodal state space (NSS) to represent the robot state in SE(3) space. Each elementary robot motion could be encoded by regulation of the state parameters via a dynamical system. This theoretically ensures that every in-process trajectory is globally feasible and stably reached to an admissible target, and the controller is of closed-form without computing 6-DoF inverse kinematics. Then, to plan the motion steps reliably, we propose an interactive (instant) goal state of the robot that transforms manipulation planning through desired path constraints into a goal-varying manipulation (GVM) problem. We detail how GVM could adaptively and smoothly plan the procedure (could proceed or rewind the process as needed) based on on-the-fly situations under dynamic or disturbed environment. Finally, we extend the above policy to characterize complete pipelines of various surgical tasks. Simulations show that our framework could smoothly solve twisted maneuvers while avoiding collisions. Physical experiments using the da Vinci Research Kit (dVRK) validates the capability of automating individual tasks including tissue debridement, dissection, and wound suturing. The results confirm good task-level consistency and reliability compared to state-of-the-art automation algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Robotic surgery

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Improving Robotic Arms through Natural Language Processing, Computer Vision, and Edge Computing

arXiv

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arXiv 2024年

作者： Sikorski, Pascal Yu, Kaleb Billadeau, Lucy Esposito, Flavio AliAkbarpour, Hadi Babaiasl, Madi Computer Science Department Saint Louis University Saint Louis United States Aerospace & Mechanical Engineering Department Saint Louis University Saint Louis United States Robotics Aerospace & Mechanical Engineering Department Saint Louis University Saint Louis United States

This paper introduces a prototype for a new approach to assistive robotics, integrating edge computing with Natural Language Processing (NLP) and computer vision to enhance the interaction between humans and robotic systems. Our proof of concept demonstrates the feasibility of using large language models (LLMs) and vision systems in tandem for interpreting and executing complex commands conveyed through natural language. This integration aims to improve the intuitiveness and accessibility of assistive robotic systems, making them more adaptable to the nuanced needs of users with disabilities. By leveraging the capabilities of edge computing, our system has the potential to minimize latency and support offline capability, enhancing the autonomy and responsiveness of assistive robots. Experimental results from our implementation on a robotic arm show promising outcomes in terms of accurate intent interpretation and object manipulation based on verbal commands. This research lays the groundwork for future developments in assistive robotics, focusing on creating highly responsive, user-centric systems that can significantly improve the quality of life for individuals with disabilities. For video demonstrations and source code, please refer to: https://***/EnhancedArmEdgeNLP. © 2024, CC BY.

关键词： Robotic arms

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Large-Scale Distributed Multidisciplinary Design Optimization of the NASA Lift-Plus-Cruise Air Taxi Concept

Large-Scale Distributed Multidisciplinary Design Optimizatio...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： van Schie, Sebastiaan P. C. Ruh, Marius L. Fletcher, Andrew Warner, Michael Sperry, Mark Scotzniovsky, Luca Orndorff, Nicholas C. Xiang, Ru Yan, Jiayao Zhao, Han Krokowski, Joshua J. Chen, J.S. Sarojini, Darshan Gill, Hyunjune Lee, Seongkyu Tagg, Andrew Anderson, Ryan Green, Eric Joseph, Cibin Ning, Andrew Cheng, Zeyu Cao, Zhi Mi, Chunting Guibert, Alexandre T. R. Cronk, Ashley Kim, H. Alicia Meng, Y. Shirley Silva, Christopher Hwang, John T. University of California San Diego 9500 Gilman Dr La Jolla CA92093 United States Department of Mechanical and Aerospace Engineering University of California San Diego 9500 Gilman Dr La Jolla CA92093 United States Department of Structural Engineering University of California San Diego 9500 Gilman Dr La Jolla CA92093 United States Aerospace and Ocean Engineering Department Virginia Tech 1600 Innovation Dr BlacksburgVA24060 United States Department of Mechanical and Aerospace Engineering University of California Davis 1 Shields Avenue DavisCA95616 United States Mechanical Engineering Brigham Young University ProvoUT84602 United States Department of Electrical & Computer Engineering San Diego State University 5500 Campanile Dr San Diego92182 United States Structural Engineering Department University of California San Diego 9500 Gilman Dr La Jolla CA92093 United States Materials Science & Engineering Program University of California San Diego 9500 Gilman Dr La Jolla CA92093 United States Pritzker School of Molecular Engineering The University of Chicago ChicagoIL60607 United States NASA Ames Research Center Moffett FieldCA94035 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Large-scale gradient-based Multidisciplinary Design Optimization (MDO) can aid in the exploration of high-dimensional design spaces for novel air vehicle concepts, thereby leading to more efficient and economic designs. This paper builds on past works where we demonstrated large-scale physics-based MDO capabilities and applied these to NASA’s lift-plus-cruise electric air taxi concept. We extend this comprehensive mid-fidelity system-level optimization problem with high(er)-fidelity subsystem-level optimizations of various aircraft systems and mission phases, with the aim of further enhancing the accuracy and scope of the aforementioned system-level optimization problem: 1) Power minimization during the transition mission phase;2) Electrical powertrain topology optimization;3) Cell chemistry modeling and thermomechanical battery pack topology optimization;4) Shell-based coupled aero-elastic wing structure optimization. An Analytical Target Cascading-like distributed MDO architecture allows us to couple the system- and subsystem-level optimizations in order to arrive at a consistent and feasible design. We find that the system-level design is most heavily impacted by the reduced battery pack-level energy densities that stem from power peaks in the mission profile. These power peaks seem to result from the inefficient lift rotor blade designs that are needed to satisfy noise constraints. We draw conclusions based on trends in our results and give recommendations for future MDO studies of electrical air taxi vehicle concepts. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Shape optimization

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Sub-optimal Perceptron Controller Using WOA Algorithm for Farming Watering Mobile Robot

Sub-optimal Perceptron Controller Using WOA Algorithm for Fa...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： M. A. Pastrana L. H. Oliveira J. Bautista Jesus Pinto-Lopera Jose Mendoza-Peñaloza Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Graduate Program University of Brasilia Brasilia DF Brazil Faculty of Engineering Systems Undergraduate Program Florencia University of the Amazonia Caquetá Colombia Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798350374575

ISBN: (纸本)9798350374582

Artificial neural networks (ANNs) are intricate mathematical models, drawing inspiration from the biological nervous system, and offering intelligence alongside nonparametric capabilities. The efficacy of ANNs heavily relies on their learning process. Heuristic search algorithms have been proposed in literature as reliable options for optimizing neural networks utilizing the Perceptron architecture. This paper presents an suboptimal neural network Perceptron training method employing the Whale Optimization Algorithm for the application of farming watering mobile robots. To achieve this, a fitness function based on system responses such as overshoot, settling Time, and steady-state Error was developed. The sub-optimal Perceptron controller was then implemented using MATLAB, CoppeliaSim software and the EVA robot, resulting in a 66.17% overshoot, a 4.7% steady-state error, and a settling time of 3.05 seconds. Moreover, the sub-optimal Perceptron controller was mapped onto a System on Chip FPGA AMD-Xilinx Zynq 7020, resulting in a hardware resources consumption of 1,870 (3.52%) Lookup table, 2 (0.9%) Digital Signal Processing blocks, 1,019 (0.96%) Flip-Flops and a power consumtion of 0.005 W. Finally, Hardware-in-the-Loop validation was performed using CoppeliaSim, Python, Universal Direct Memory Access, and the EVA robot. The results showed an overshoot of 94.83%, a settling time of 2 seconds, and a steady-state error of 4.5%.

关键词： Software algorithms Signal processing algorithms Software Hardware Whale optimization algorithms Steady-state Mobile robots MATLAB Farming Python

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Electro-humidity responsive soft actuators based on cellulose nanofibers-nanocrystals for bioinspired applications

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Science China Technological Sciences 2025年第7期68卷 1-9页

作者： Wang, Fan Qi, Ruibin Wu, Yujiao Li, Qinchuan Zhang, Junhui Park, Sukho School of Mechanical Engineering Zhejiang Sci-Tech University Hangzhou China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou China Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea

Multifunctional responsive actuators have garnered considerable attention for their potential applications in soft robots, wearable devices, smart displays, environmental sensing, and biomimetic systems. Herein, we present a multifunctional color-changing ionic soft actuator that integrates electrical actuation and humidity-induced color-changing functionalities, fabricated using carboxylated cellulose nanofibers, ionic liquids, polyvinyl alcohol, cellulose nanocrystals, and poly(ethylene glycol) diacrylate. The electro-humidity responsive actuator exhibited remarkable actuation performance, including a maximum tip displacement (10.2 mm), low driving voltage (as low as 1.0 V), high operational stability (95.2% reliability after 2000 actuation cycles), broad working frequency range (0.2–3.0 Hz), and exceptional tolerance to humid environments (90% relative humidity). In addition, the actuator showcased reversible and integrated color-changing capabilities. These features enabled the design of innovative devices, such as biomimetic flowers and smart color-changing windows with tunable optical properties. Consequently, this multifunctional actuator provides a promising platform for applications in soft robots, optical anti-counterfeiting systems, information storage materials, and intelligent home technologies.

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Data-Driven Batch Localization and SLAM Using Koopman Linearization

arXiv

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arXiv 2023年

作者： Guo, Zi Cong Dumbgen, Frederike Forbes, James R. Barfoot, Timothy D. University of Toronto Robotics Institute TorontoON Canada Department of Mechanical Engineering McGill University MontrealQC Canada

We present a framework for model-free batch localization and SLAM. We use lifting functions to map a controlaffine system into a high-dimensional space, where both the process model and the measurement model are rendered bilinear. During training, we solve a least-squares problem using groundtruth data to compute the high-dimensional model matrices associated with the lifted system purely from data. At inference time, we solve for the unknown robot trajectory and landmarks through an optimization problem, where constraints are introduced to keep the solution on the manifold of the lifting functions. The problem is efficiently solved using a sequential quadratic program (SQP), where the complexity of an SQP iteration scales linearly with the number of timesteps. Our algorithms, called Reduced Constrained Koopman Linearization Localization (RCKL-Loc) and Reduced Constrained Koopman Linearization SLAM (RCKL-SLAM), are validated experimentally in simulation and on two datasets: one with an indoor mobile robot equipped with a laser rangefinder that measures range to cylindrical landmarks, and one on a golf cart equipped with RFID range sensors. We compare RCKL-Loc and RCKL-SLAM with classic model-based nonlinear batch estimation. While RCKLLoc and RCKL-SLAM have similar performance compared to their model-based counterparts, they outperform the model-based approaches when the prior model is imperfect, showing the potential benefit of the proposed data-driven technique. Copyright © 2023, The Authors. All rights reserved.

关键词： Quadratic programming

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Cross-coupling based Finite-time Synchronization Control of the Automated Fiber Placement System 37

Cross-coupling based Finite-time Synchronization Control of ...

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37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022

作者： Zhang, Ronghua Wang, Yaonan Tan, Haoran Xie, Wenfang Jiang, Yiming Xie, He Liu, Li Hunan University College of Electrical and Information Engineering Changsha China National Engineering Research Center of RVC Changsha China Concordia University Department of MechanicalIndustrial and Aerospace Montreal Canada Hunan University School of Robotics Changsha China

ISBN: (纸本)9781665465366

The application of multi-robots in automated fiber placement system (AFPS) makes it possible to manufacture complex composite components. For high-quality fiber placement tasks, the synchronization of multi-robots is necessary. In this work, a novel cross-coupling based finite-time synchronization control (CFSC) algorithm for a particular AFPS is proposed. In this algorithm, the synchronization function and cross-coupling technology are employ to describe the synchronization and comprehensive trajectory tracking performance of the system. Two coupled errors based sliding variables are designed. The stability of the AFPS is proved by Lyapunov theory, which indicate that the pose errors and synchronization errors of the system can simultaneously finite-time convergence to zero. The simulation demonstrate that the effectiveness of the CFSC algorithm. © 2022 IEEE.

关键词： Synchronization

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Spatio-Temporal Object Persistence Modeling for Long-Term Mapping and Navigation Planning

SSRN

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SSRN 2023年

作者： Symmank, Meredith Leeann Anderson, Robert Blake Suarez, Christopher William Pryor, Mitchell Wayne Nuclear and Applied Robotics Group Walker Department of Mechanical Engineering University of Texas AustinTX United States

Mobile robots increasingly operate in real-world environments that are subject to change over time. Robots that maintain up-to-date, accurate representations of their environment can more robustly perform long-term autonomous navigation and planning tasks. We propose Spatio-temporal Object Persistence (STOP) modeling so robots can adapt maps over long periods of time and predict changes in their environments. STOP models enable a robot to assign temporal characteristics to recognized objects based on their observed persistence in the world. A robot develops these identifying characteristics by iteratively estimating parameters for a Weibull distribution survival model using recursive Bayesian Survival Analysis with Markov Chain Monte Carlo methods. The parameters of the model provide temporally identifying features to classify objects. These characteristics allow a robot to estimate the true lifespan of objects and predict when they will leave the environment so it can adapt its map. This allows for more intelligent planning and navigation for future operations. Furthermore, once the robot develops temporal class characteristics, it can transfer and apply these characteristics to objects in dynamically similar environments, thus allowing the robot to adapt more quickly to new operational spaces. We demonstrate the efficacy of STOP models for adapting a map over time in a semi-static environment. Our results show that the learned models predict the temporal behavior of objects in the world and transfer to unknown, but temporally similar operation spaces © 2023, The Authors. All rights reserved.

关键词： Monte Carlo methods

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Robust Safe Control with Multi-Modal Uncertainty

arXiv

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arXiv 2023年

作者： Wei, Tianhao Ma, Liqian Pandya, Ravi Liu, Changliu Robotics Institute Carnegie Mellon University United States The Department of Mechanical Engineering Ts-inghua University China

Safety in dynamic systems with prevalent uncertainties is crucial. Current robust safe controllers, designed primarily for uni-modal uncertainties, may be either overly conservative or unsafe when handling multi-modal uncertainties. To address the problem, we introduce a novel framework for robust safe control, tailored to accommodate multi-modal Gaussian dynamics uncertainties and control limits. We first present an innovative method for deriving the least conservative robust safe control under additive multi-modal uncertainties. Next, we propose a strategy to identify a locally least-conservative robust safe control under multiplicative uncertainties. Following these, we introduce a unique safety index synthesis method. This provides the foundation for a robust safe controller that ensures a high probability of realizability under control limits and multi-modal uncertainties. Experiments on a simulated Segway validate our approach, showing consistent realizability and less conservatism than controllers designed using uni-modal uncertainty methods. The framework offers significant potential for enhancing safety and performance in robotic applications. © 2023, CC BY.

关键词： Controllers

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Fiber Optic Sensor Improves Displacement Measurement in Dielectric Elastomers Actuators

Fiber Optic Sensor Improves Displacement Measurement in Diel...

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IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications, MESA

作者： Alexandre Bernardo Santos Da Silva Gabriel Escher Pires Mendes Arnaldo Gomes Leal Claysson B. S. Vimieiro Camilo Arturo Rodríguez Díaz Rafhael Milanezi de Andrade Graduate Program of Mechanical Engineering Universidade Federal do Espírito Santo Vitória Brazil Department of Mechanical Engineering Universidade Federal do Espírito Santo Vitória Brazil Graduate Program of Mechanical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Graduate Program of Electrical Engineering Universidade Federal do Espírito Santo Vitória Brazil Graduate Program of Mechanical Engineering Universidade Federal do Espírito Santo Vitória ES Brazil

ISBN: (数字)9798331516239

ISBN: (纸本)9798331516246

Currently, developments in mechatronics have enabled the creation of compliant actuators and synthetic muscles, surpassing the constraints of inflexible actuators in assistive robotics systems. Dielectric elastomer actuators (DEAs) are comprised of an elastomer layer situated amidst two flexible electrodes, able to change dimensions under the influence of an electric voltage. While DEAs can function as autonomous sensors due to their viscoelastic behavior, accurately measuring actuator displacement continues to be an unresolved challenge. In this study, we introduce the development and assessment of a fiber-constrained dielectric elastomer actuator (FCDEA) with embedded optical fiber sensors for displacement measurement through optical potential difference. The DEAs were fabricated with VHB 4910, conductive carbon grease, and PETG as constrain fiber to restrict its displacement to the vertical direction. Silica optical fiber was integrated in the PETG strips and clamps to measure the actuator deformation upon activation. Different fabrication parameters of DEAs were investigated to obtain greater strain rates. DEAs with 90 mm x 90 mm, stretch (λ) = 3.6, and load (τ) = 120 kPa, and 90 mm x 110 mm, λ=3.6, and τ=120 kPa, presented the highest deformation capacity, with 90% and 80%, respectively. Moreover, results showed great linearity between the DEA deformation and optical potential, indicating the proposed configuration is suitable for displacement measurement.

关键词： Optical fibers Temperature measurement Optical fiber sensors Mechatronics Deformation Optical device fabrication Linearity Displacement measurement Optical variables measurement Muscles

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