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Adaptive Control Lyapunov Function-Based Controller Using Fixed Point Iteration

Adaptive Control Lyapunov Function-Based Controller Using Fi...

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international symposium on Applied computational intelligence and Informatics ( SACI)

作者： Massimo Stefanoni Dominik Csík Peter Sarcevic Ákos Odry József K. Tar Doctoral School of Applied Informatics and Applied Mathematics Obuda University Budapest Hungary Department of Mechatronics and Automation Faculty of Engineering University of Szeged Szeged Hungary John von Neumann Faculty of Informatics Obuda University Budapest Hungary

ISBN: (数字)9798350329520

ISBN: (纸本)9798350329537

The Proportional Integral Derivative (PID), the Computed Torque Control (CTC), the Fuzzy Logic (FL), and the Artificial Neural Network (ANN) controllers are some examples of methods widely used in the industrial sectors for control purposes. All of them have been largely developed and investigated, but besides their advantages, they have some drawbacks which have not been completely solved yet. Other types of approaches, especially used in robotics, are classical adaptive methods such as the Adaptive Inverse Dynamics Control (AIDC), the Adaptive Slotine-Li Control (ASCL), and the Model Reference Adaptive Controller (MRAC). They need a formally accurate robot model and they fail in the presence of unknown external disturbances or friction. This work aims to propose a new Fixed Point Iteration-based (FPI) adaptive controller that applies Control Lyapunov Function for kinematic design, and a multi-dimensional generalization of the Rodrigues formula for adaptation. The first one is derived using the error of the second derivative of the generalized coordinates and tries to move the error to zero exponentially. The second one is used to develop an Adaptive Deformation function to compensate for the inaccurate dynamic model where the new output for the vector of the second derivative of the generalized coordinates is obtained by smooth rotations. The concept was simulated by using Julia code which demonstrated the feasibility of the idea providing after the transient an oscillating error which ranges between -0.005 and 0.004 rad.

关键词： Fuzzy logic Adaptation models Deformation Service robots Robot kinematics Torque control Artificial neural networks

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GA3C Reinforcement Learning for Surgical Steerable Catheter Path Planning

GA3C Reinforcement Learning for Surgical Steerable Catheter ...

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ieee international Conference on robotics and automation (ICRA)

作者： Alice Segato Luca Sestini Antonella Castellano Elena De Momi Department of Electronics Politecnico di Milano Milano Italy Neuroradiology Unit and CERMAC Vita-Salute San Raffaele University and IRCCS Ospedale San Raffaele Milan Italy

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Path planning algorithms for steerable catheters, must guarantee anatomical obstacles avoidance, reduce the insertion length and ensure the compliance with needle kinematics. The majority of the solutions in literature focuses on graph based or sampling based methods, both limited by the impossibility to directly obtain smooth trajectories. In this work we formulate the path planning problem as a reinforcement learning problem and show that the trajectory planning model, generated from the training, can provide the user with optimal trajectories in terms of obstacle clearance and kinematic constraints. We obtain 2D and 3D environments from MRI images processing and we implement a GA3C algorithm to create a path planning model, able to generalize on different patients anatomies. The curvilinear trajectories obtained from the model in 2D and 3D environments are compared to the ones obtained by A* and RRT* algorithms. Our method achieves state-of-the-art performances in terms of obstacle avoidance, trajectory smoothness and computational time proving this algorithm as valid planning method for complex environments.

关键词： Trajectory Needles Three-dimensional displays Learning (artificial intelligence) Catheters Kinematics

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Research on the Application of Deep Learning Algorithm in Visual Perception and Recognition of Artificial intelligence Robot

Research on the Application of Deep Learning Algorithm in Vi...

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Electrical, automation and Computer Engineering (ICEACE), international Conference on

作者： Yujia Li Siheng Ren Na Yang School of Metallurgy Northeastern University Shenyang China Space Engineering University Beijing China

ISBN: (数字)9798350368208

ISBN: (纸本)9798350368215

With the rapid advancement of science and technology, artificial intelligence (AI) has emerged as a focal point in the realm of technology. Among its core branches, deep learning endows computers with formidable data processing capabilities by emulating the cognitive processes of the human brain. This work delves into the application of deep learning in robotic visual perception, encompassing areas such as image recognition, object detection, and motion planning, thereby illustrating how deep learning algorithms can markedly enhance a robot’s visual perception capabilities. To validate these enhancements, the YOLOv5 model was employed for real-time object detection, which was further integrated with the A* algorithm for robotic path planning. The outcomes demonstrate that the YOLOv5-based object detection algorithm performs admirably in complex environments. Collectively, this research furnishes fresh perspectives and methodologies for the progression of robotics technology in the future.

关键词： Deep learning YOLO Computers Heuristic algorithms computational modeling Real-time systems Path planning Vehicle dynamics Robots Visual perception

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Research on Propeller Blades Sanding Degree Recognition Algorithm Based on Improved DeepLabV3+ Network

Research on Propeller Blades Sanding Degree Recognition Algo...

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ieee international Conference on Mechatronics, robotics and automation (ICMRA)

作者： Siying Cao Baocheng Yu Wenxia Xu College of Computer Science and Engineering College of Artificial Intelligence Wuhan Institute of Technology Wuhan China

ISBN: (数字)9798350352474

ISBN: (纸本)9798350352481

In the overhaul process of airplane propeller blades, the foam filling on the shoulder of the blades needs to be ground off. To achieve automated recognition of the sanding degree of propeller blades, an image semantic segmentation algorithm based on the improved DeepLabV3+ network is proposed. The algorithm adopts a lightweight network, MobileNetV2, to replace the original backbone network of DeepLabv3+, reducing computational complexity. The atrous spatial pyramid pooling (ASPP) feature extraction module is improved by replacing the atrous convolution with depthwise separable convolution and introducing the Convolutional Block Attention Module(CBAM), enhancing the overall training efficiency and segmentation accuracy of the model. Group normalization (GN) is used instead of batch normalization (BN) to further improve model performance. The experimental results on the dataset collected from the propeller blades sanding site show that the proposed algorithm achieves a mean intersection over union (MioU) of 91.40%, a mean pixel accuracy (MPA) of 95.63%, and an inference speed (FPS) of 33.88. Compared to the current mainstream segmentation algorithms such as DeepLabV3+, PSPNet, and HRNet, the improved algorithm demonstrates enhanced segmentation accuracy and inference speed.

关键词： Training Airplanes Accuracy Image recognition Propellers Convolution Blades Semantic segmentation Inference algorithms robotics and automation

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Model-Based Shape Estimation and Closed-Loop Control of Magnetic Continuum Robot Based on Monocular Vision

Model-Based Shape Estimation and Closed-Loop Control of Magn...

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ieee international Conference on robotics and Biomimetics

作者： Junfeng Zhu Yuanrui Huang Jian Chen Hongbin Liu State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences (CASIA) Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Centre of AI and Robotics Hong Kong Institute of Science Innovation Chinese Academy of Sciences School of Biomedical Engineering and Imaging Sciences King's College London UK

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Magnetic continuum robots (MCRs) show promising potential for applications in narrow lumens, such as vascular interventions. Accurate shape sensing of these robots is crucial for the success of interventional surgeries. However, the submillimeter dimensions of MCRs poses significant challenges for integrating additional sensors. An alternative approach is shape estimation from images, yet the lack of precise MCR kinematics can make this process time-consuming. In this work, we propose a novel MCR design featuring a rectangular tip capable of specific planar bending, along with a corresponding kinematic model and a mechanical model. Additionally, we introduce a model-based shape estimation method that enables the estimation of the MCR's shape from a single-view image without the need for external markers. Experimental results demonstrate that our method can estimate an MCR's shape with a mean absolute error (MAE) of $\mathbf{0.58}\pm \mathbf{0.41}\mathbf{mm}$ within 85ms, facilitating real-time application. Furthermore, closed-loop control based on this method has achieved an end position error below 11% of the tip's total length, highlighting the accuracy and practicality of our approach for surgical interventions.

关键词： Solid modeling Shape computational modeling Magnetic resonance imaging Estimation Kinematics Robot sensing systems Real-time systems Continuum robots Magnetosphere

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Lean disassembly line layout, and network simulation models

Lean disassembly line layout, and network simulation models

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ieee international symposium on Electronics and the Environment

作者： P.G. Ranky L.C. Morales R.J. Caudill Department of Industrial and Manufacturing Systems Engineering MERC New Jersey Institute of Technology Newark NJ USA The Department of Industrial and Manufacturing Systems Engineering New Jersey Institute of Technology Newark NJ USA Department of Industrial and Manufacturing Engineering MERC NJIT Newark NJ USA

The purpose of this research is to create a simulation method and validated cases, that enable disassembly enterprises to experiment with different computer networking solutions, and protocols for electronically supported manual, and optionally automated robotized disassembly workstations (integrated into a disassembly line), to experiment with different disassembly process layout and cell/line design solutions, and to provide electronic support systems for designers and managers for evaluating 'what if?' scenarios, when developing such systems. This simulation project extends our Web-enabled Virtual Disassembly Manager (webVDM) project for electronic product/process designers, disassembly line managers and operators. webVDM is a major MERC/NJIT R&D group effort, supported by several funding agencies, companies and institutions and their hard working staff, and our RAs (Research Assistants).

关键词： computational modeling Project management Research and development management Computer simulation Computer networks Protocols robotics and automation Workstations Computer network management Process design

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Online-Adaptive Anomaly Detection for Defect Identification in Aircraft Assembly

Online-Adaptive Anomaly Detection for Defect Identification ...

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ieee international Conference on automation Science and Engineering (CASE)

作者： Siddhant Shete Dennis Mronga Ankita Jadhav Frank Kirchner Robotics Innovation Center of German Research Center for Artificial Intelligence GmbH (DFKI) Bremen Germany Robotics Group of the University of Bremen Germany

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Anomaly detection deals with detecting deviations from established patterns within data. It has various applications like autonomous driving, predictive maintenance, and medical diagnosis. To improve anomaly detection accuracy, transfer learning can be applied to large, pre-trained models and adapt them to the specific application context. In this paper, we propose a novel framework for online-adaptive anomaly detection using transfer learning. The approach adapts to different environments by selecting visually similar training images and online fitting a normality model to EfficientNet features extracted from the training subset. Anomaly detection is then performed by computing the Mahalanobis distance between the normality model and the test image features. Different similarity measures (SIFT/FLANN, Cosine) and normality models (MVG, OCSVM) are employed and compared with each other. We evaluate the approach on different anomaly detection benchmarks and data collected in controlled laboratory settings. Experimental results showcase a detection accuracy exceeding 0.975, outperforming the state-of-the-art ET-NET approach.

关键词： Training Adaptation models Accuracy computational modeling Transfer learning Benchmark testing Feature extraction Aircraft manufacture Aircraft Anomaly detection

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A formal approach to reactive system design: unmanned aerial vehicle flight management system design example

A formal approach to reactive system design: unmanned aerial...

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ieee international symposium on Computer Aided Control System Design (CACSD)

作者： T.J. Koo B. Sinopoli A. Sangiovanni-Vincentelli S. Sastry Robotics and Intelligent Machines Laboratory Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA

This paper presents a formal methodology for the design, implementation and validation of reactive systems. The methodology has been applied to the design of a flight management systems for a model helicopter in the BEAR project. POLIS, a design tool developed at the University of California at Berkeley, is extensively used. The automation of the design problem and the validation techniques provided by this tool allow one to shorten prototyping time and to prove the correctness of the properties of the system. Automatic code generation guarantees error free implementation, which is fundamental in safety critical applications. Simulation of the entire design is performed using Ptolemy, a hierarchical heterogeneous simulation environment.

关键词： Unmanned aerial vehicles Flexible manufacturing systems Safety Control systems Intelligent robots Timing computational modeling Automatic control Engineering management Intelligent vehicles

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Selection of kinematic requirements for RFPT-based adaptive anaesthesia control

Selection of kinematic requirements for RFPT-based adaptive ...

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international symposium on Applied computational intelligence and Informatics ( SACI)

作者： Bertalan Csanádi József K. Tar Doctoral School of Applied Informatics and Applied Mathematics John von Neumann Faculty of Informatics Obuda University Budapest Hungary Research and Innovation Center Antal Bejczv Center for Intelligent Robotics (ABC iRob)

ISBN: (纸本)9781509023813

The automatic control of the level of hypnosis is a significant part of anaesthesia during surgical operations. The prevalent patient models consist of a four variable set of ordinary differential equations with a driving term, the Propofol infusion rate. One of the directly observable quantities is the Bispectral Index that is related to one of the state variables by a nonlinear function with patient-dependent parameters that have quite significant interpatient variability and normally cannot be known in advance. Furthermore, this index can suffer abrupt variations during the surgical operations. This fact makes the application of classical control approaches difficult because they operate with state feedback gains and state observers. The significant model uncertainties need either robust or adaptive solutions. A novel alternative of the Lyapunov function based adaptive control design, i.e. the Robust Fixed Point Transformation (RFPT)-based adaptive control can solve such problems by replacing the complicated state space model with a simple affine function instead of the use of state observers. This method strictly separates the kinetic and dynamic aspects of the controlled motion so allows arbitrary kinetic prescription for the tracking error relaxation. Via numerical (“in silico”) simulations it is shown how the four investigated plausible kinetic options (namely the “PD-type”, “PID-type”, “Error Metrics-based PD-type”, and “Error Metrics-based PID-type” prescribed tracking error relaxation) concern the quality of the control. It is found that two different options, the “PD-type” and the “PID-type” ones, have almost equally good results while the other ones seem to be less efficient.

关键词： Adaptation models Indexes Drugs Brain models Mathematical model Adaptive control

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Proactive Interaction Framework for Intelligent Social Receptionist Robots

Proactive Interaction Framework for Intelligent Social Recep...

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ieee international Conference on robotics and automation (ICRA)

作者： Yang Xue Fan Wang Hao Tian Min Zhao Jiangyong Li Haiqing Pan Yueqiang Dong Baidu Natural Language Processing Department Baidu Research Baidu AI Interaction Design Lab

Proactive human-robot interaction (HRI) allows the receptionist robots to actively greet people and offer services based on vision, which has been found to improve acceptability and customer satisfaction. Existing approaches are either based on multi-stage decision processes or based on end-to-end decision models. However, the rule-based approaches require sedulous expert efforts and only handle minimal pre-defined scenarios. On the other hand, existing works with end-to-end models are limited to very general greetings or few behavior patterns (typically less than 10). To address those challenges, we propose a new end-to-end framework, the TransFormer with Visual Tokens for Human-Robot Interaction (TFVT-HRI)¹. The proposed framework extracts visual tokens of relative objects from an RGB camera first. To ensure the correct interpretation of the scenario, a transformer decision model is then employed to process the visual tokens, which is augmented with the temporal and spatial information. It predicts the appropriate action to take in each scenario and identifies the right target. Our data is collected from an in-service receptionist robot in an office building, which is then annotated by experts for appropriate proactive behavior. The action set includes 1000+ diverse patterns by combining language, emoji expression, and body motions. We compare our model with other SOTA end-to-end models on both offline test sets and online user experiments in realistic office building environments to validate this framework. It is demonstrated that the decision model achieves SOTA performance in action triggering and selection, resulting in more humanness and intelligence when compared with the previous reactive reception policies.

关键词： Visualization computational modeling Buildings Semantics Diversity reception Human-robot interaction Reinforcement learning

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