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Flexible control of a grasping object with posture error

Flexible control of a grasping object with posture error

引用

ieee international Conference on Fuzzy Systems (FUZZ-ieee)

作者： Y. Hasegawa M. Higashiura T. Fukuda Department of Micro System Engineering University of Nagoya Japan Department of Mechano Informatics System Engineering University of Nagoya Japan Center for Cooperative Research in Advanced Science and Technology University of Nagoya Japan

Proposes adjusting methods of a regrasping strategy according to position and posture errors of a grasping object. We have already derived a generation algorithm for the regrasping strategy by evolutionary programming. The regrasping strategy however becomes inapplicable when the relative position and posture between a hand and an object is not same as those in numerical simulation. We therefore propose some adjusting methods which can change the intermediate position and posture of a grasping object. This method can avoid the limitation of joint work area and fingertip's slip so that it could extend the tolerable area of the position and posture error. We show its effectiveness for the regrasping motion with numerical simulations and experiments.

关键词： Error correction Grasping Fingers Robots Systems engineering and theory Numerical simulation Solids Genetic programming robotics and automation Robust control

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Improved bacterial foraging strategy for controller optimization applied to robotic manipulator system

Improved bacterial foraging strategy for controller optimiza...

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ieee international Conference on Computer-Aided Design

作者： Leandro dos Santos Coelho Camila da Costa Silveira Automation and System Laboratory Pontifical Catholic University of Parana Curitiba Parana Brazil

During the course of evolution, colonies of ants, bees, wasps, bacteria and termites have developed sophisticated behavior, intricate communication capabilities, decentralized colony control, group foraging strategies and a high degree of worker cooperation when tackling tasks. Utilizing these capabilities, any bio-inspired optimization techniques using analogy of swarming principles and social behavior in nature — swarm intelligence — have been adopted to solve a variety of engineering and robotics problems. In this paper, new approaches of bacterial colony optimization method with variable speed based on uniform, Gaussian, and Cauchy probability distribution were tested. Bacterial colony, a swarm intelligence methodology, is evaluated for a problem of optimization of a PID (proportional-integral-derivative) multivariable controller. The simulation results are compared with classical bacterial colony approach with constant velocity for a case study of control of a robotic manipulator system with two degree of freedom.

关键词： Microorganisms Control systems Manipulators Communication system control Ant colony optimization Particle swarm optimization Optimization methods Intelligent robots Probability distribution Testing

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Evaluating Contemporary Machine Learning and Deep Learning Strategies for Intrusion Detection

Evaluating Contemporary Machine Learning and Deep Learning S...

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Control & automation, Electronics, robotics, Internet of Things, and Artificial intelligence (CERIA), ieee international Conference on

作者： Riza Sauqi Valasev Anas Rachmadi Priambodo Ratih Nur Esti Anggraini Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798331511166

ISBN: (纸本)9798331511173

As cyber threats evolve with increasing complexity, the imperative for advanced Network Intrusion Detection Systems (NIDS) becomes paramount. This study offers a rigorous comparative analysis of traditional Machine Learning (ML) algorithms and cutting-edge Deep Learning (DL) techniques within the framework of the contemporary CICIDS-2018 dataset, aimed at evaluating their proficiency in network intrusion detection. The machine learning classifiers used are K-Nearest Neighbors, Logistic Regression, Random Forest, and Support Vector Machines, against a hybrid DL model combining Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU). The study reveals that while ML algorithms maintain the benefit of interpretability and lower computational demands, the hybrid CNN-GRU model showcases exceptional capability in discerning intricate and latent patterns indicative of intrusive activities, hence yielding superior detection accuracy and demonstrating resilience against overfitting. The complex dynamics of network security require adaptive model selection, and this comparison research shows the efficacy of merging ML and DL approaches. The results affirm the viability of deploying a hybrid analytical framework that capitalizes on the strengths of both ML and DL, leveraging the comprehensive and diverse nature of the CICIDS-2018 dataset to bolster the security posture of digital infrastructures against the burgeoning wave of cyber threats.

关键词： Deep learning Support vector machines Adaptation models Machine learning algorithms computational modeling Network intrusion detection Classification algorithms Convolutional neural networks Robots Resilience

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Yolov9-Powered Bangla License Plate Recognition: A Comparative Analysis for Optimized Performance in Localized Contexts

Yolov9-Powered Bangla License Plate Recognition: A Comparati...

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Control & automation, Electronics, robotics, Internet of Things, and Artificial intelligence (CERIA), ieee international Conference on

作者： Akash Das K. M. Asieb Hasan Dept. of Computer Science Federation University Australia Ballarat Australia Glichin' Dhaka Bangladesh

ISBN: (数字)9798331511166

ISBN: (纸本)9798331511173

This study presents an advanced approach to Bangla license plate recognition using YOLOv9, the latest iteration in the YOLO (You Only Look Once) object detection series. We employ a comprehensive dataset of Bangladeshi vehicle license plates, encompassing 12 vehicle categories across four major cities. The dataset underwent extensive preprocessing, including merger, format conversion, and augmentation to optimize it for YOLOv9 architecture. We evaluate five YOLOv9 model variants (YOLOv9-T, YOLOv9-S, YOLOv9-M, YOLOv9-C, and YOLOv9-E) on this dataset, analyzing their performance in terms of accuracy, efficiency, and generalization capability. Our results demonstrate a clear correlation between model size and detection accuracy, with YOLOv9-E achieving the highest F1 score of 0.9550. We observe a trade-off between model efficiency and accuracy, with larger models offering superior detection capabilities at the cost of increased computational demands. The study provides insights into the optimal model selection for various real-world scenarios, balancing between high-throughput requirements and accuracy priorities.

关键词： YOLO Accuracy Costs Correlation Corporate acquisitions computational modeling Urban areas Internet of Things Convolutional neural networks License plate recognition

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A Model-Free Approach to Meta-Level Control of Anytime Algorithms

A Model-Free Approach to Meta-Level Control of Anytime Algor...

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ieee international Conference on robotics and automation (ICRA)

作者： Justin Svegliato Prakhar Sharma Shlomo Zilberstein College of Information and Computer Sciences University of Massachusetts Amherst MA USA

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Anytime algorithms offer a trade-off between solution quality and computation time that has proven to be useful in autonomous systems for a wide range of real-time planning problems. In order to optimize this trade-off, an autonomous system has to solve a challenging meta-level control problem: it must decide when to interrupt the anytime algorithm and act on the current solution. Prevailing meta-level control techniques, however, make a number of unrealistic assumptions that reduce their effectiveness and usefulness in the real world. Eliminating these assumptions, we first introduce a model-free approach to meta-level control based on reinforcement learning and prove its optimality. We then offer a general meta-level control technique that can use different reinforcement learning methods. Finally, we show that our approach is effective across several common benchmark domains and a mobile robot domain.

关键词： Learning (artificial intelligence) Autonomous systems Planning Heuristic algorithms computational modeling Real-time systems Uncertainty

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HapNet: A Learning-Based Haptic-Kinematic Model for Surface Material Classification in Robot Perception

HapNet: A Learning-Based Haptic-Kinematic Model for Surface ...

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ieee international Conference on automation Science and Engineering (CASE)

作者： Tianqiang Yan Tiansheng Xu Tianwei Zhang Zhenglong Sun Future Network of Intelligence Institute and School of Science and Engineering The Chinese University of Hong Kong Shenzhen Faculty of Natural Sciences Imperial College London Shenzhen Institute of Artificial Intelligence and Robotics for Society

The advancement of modern robotic systems is inseparable from the development of artificial sensory modules and functions that provide robots with human-like perception. Among these, haptic sensation is of vital importance for robot interaction with the environment. Many research works have been conducted in the past decades to enable robots to sense the environment, especially in the area of surface material classification. This paper offers a learning-based low-cost but high computational efficient method adopting multiple kinematic modalities, namely the haptic-kinematic data. We introduce a haptic surface material dataset and propose a kinematics-motivated haptic surface material classification network (Hap-Net) trained and tested on our dataset. The results demonstrate the feasibility and robustness of a purely kinematic haptic scheme without the need for other perceptual modalities. The source codes, datasets, etc., have been made publicly available as an open-source package 1 1 https://***/henryyantq/haptic-kinematics.

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CAD/simulation for dynamic environments

CAD/simulation for dynamic environments

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ieee international symposium on Intelligent Control (ISIC)

作者： H. Fok M.R. Kabuka Department of Electrical & Computer Engineering University of Miami Coral Gables FL USA

The architecture and working of a flexible multiple mobile robot system (MMRS) are described. The use of a path network to define allowed paths for the mobile robots is proposed. This greatly simplifies the detection of possible collisions between the robots and the problem of replanning the motion. The MMRS is divided into three main components standard pattern, central controller, and individual mobile robot. The architecture of the proposed MMRS is presented and its operation discussed in detail. Efficient control algorithms for both the central controller and individual mobile robots are developed and presented. A CAD/simulation system for the design and evaluation of the MMRS is developed. Simulation results to emphasize the validity of the system are presented.< >

关键词： Mobile robots Centralized control Robot kinematics Motion detection Orbital robotics computational modeling Design automation Wire Ferrites Navigation

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Petri net-based approach to intelligent control synthesis of FMS

Petri net-based approach to intelligent control synthesis of...

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international Conference on Emerging Technologies and Factory automation (ETFA)

作者： F. Capkovic Institute of Control Theory and Robotics Slovak Academy of Sciences Bratislava Slovakia

Because the classical control theory does not give satisfactory results in the DEDS (discrete event dynamic systems) control systems synthesis, especially in analytical terms, and because such systems are very important in human life-e.g. flexible manufacturing systems (FMS), transport systems, communications systems, etc.-another approaches are wanted. The main aim of this paper is to point out a simple approach leading to a very simple dealing with the FMS (as a kind of the DEDS) modelling and intelligent control problems solving. On that way imbedding some results of applied artificial intelligence, especially the rule-based knowledge representation and simple form of automatic reasoning, is used.

关键词： Intelligent control Flexible manufacturing systems Integrated circuit modeling Control system synthesis Analog integrated circuits Control theory Mathematical model Automatic control Vectors Robots

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Hybrid Differential Dynamic Programming for Planar Manipulation Primitives

Hybrid Differential Dynamic Programming for Planar Manipulat...

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ieee international Conference on robotics and automation (ICRA)

作者： Neel Doshi Francois R. Hogan Alberto Rodriguez Intelligence Community Postdoctoral Research Fellowship Program Massachusetts Institute of Technology Cambridge MA Dept. of Mechanical Engineering Massachusetts Institute of Technology

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

We present a hybrid differential dynamic programming (DDP) algorithm for closed-loop execution of manipulation primitives with frictional contact switches. Planning and control of these primitives is challenging as they are hybrid, under-actuated, and stochastic. We address this by developing hybrid DDP both to plan finite horizon trajectories with a few contact switches and to create linear stabilizing controllers. We evaluate the performance and computational cost of our framework in ablations studies for two primitives: planar pushing and planar pivoting. We find that generating pose-to-pose closed-loop trajectories from most configurations requires only a couple (one to two) hybrid switches and can be done in reasonable time (one to five seconds). We further demonstrate that our controller stabilizes these hybrid trajectories on a real pushing system. A video describing our work can be found at https://***/YGSe4cUfq6Q.

关键词： Trajectory Planning Contacts Heuristic algorithms Force Convergence Friction

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An application of the 4-parameter controller to the robot payload variation problem

An application of the 4-parameter controller to the robot pa...

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ieee international symposium on Intelligent Control (ISIC)

作者： K.P. Valavanis C.A. Jacobson B. Gold Department of Electrical and Computer Engineering Northeastern University Boston MA USA Department of Electrical Engineering and ComputerEngineering Northeastern University Boston MA USA

The authors describe the design of a diagnostic system to maintain high performance of robotic manipulators in the face of payload variations. The novel application of failure diagnostic methods to the problem of detecting abrupt payload variations in robots is introduced. Application of the four-parameter controller to the simultaneous design of the feedback control and diagnostic systems using a computed torque controller is based on the key concept of treating the study of payload variations as a failure diagnostic problem. The proposed methodology has been tested on a PUMA-560 robot arm in a three-degrees-of-freedom configuration. The simulation results obtained demonstrate the promise of the methodology.< >

关键词： Robot control Payloads Control systems Torque control Automatic control Manipulator dynamics Feedback control computational modeling robotics and automation Jacobian matrices

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