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Early Access Articles

Early Access articles are new content made available in advance of the final electronic or print versions and result from IEEE's Preprint or Rapid Post processes. Preprint articles are peer-reviewed but not fully edited. Rapid Post articles are peer-reviewed and edited but not paginated. Both these types of Early Access articles are fully citable from the moment they appear in IEEE Xplore.

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Displaying Results 1 - 25 of 67
  • Assignment Algorithms for Modeling Resource Contention in Multirobot Task Allocation

    Publication Year: 2015 , Page(s): 1 - 12
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1895 KB)  

    This paper considers multirobot task allocation problems where the estimated costs for performing tasks are interrelated, and the overall team objective need not be a standard sum-of-costs (or utilities) model, enabling straightforward treatment of the additional costs incurred by resource contention. In the model we introduce, a team may choose one of a set of shared resources to perform a task (e.g., several routes to reach a destination), and interference is modeled when multiple robots use the same resource. We show that the general problem is NP-hard, and investigate specialized subinstances with particular cost structures. For the general problem, we describe an exact algorithm which finds an optimal assignment in a reasonable time on small instances. Aiming at larger problems, we turn two particular subinstances, introducing an two algorithms that find assignments quickly even for problems of considerable size, the first being optimal, the second being an approximation algorithm but also producing high-quality solutions with bounded suboptimality. View full abstract»

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  • A Spatial Calibration Model for Nanotube Film Quality Prediction

    Publication Year: 2015 , Page(s): 1 - 15
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3414 KB)  

    A carbon nanotube (CNT) film, which is drawn from a CNT array, is a spatially distributed thin film with unique and appealing properties. Novel devices have been developed based on CNT films. The anisotropy of a CNT film, which is a spatially distributed quality index, is difficult to measure in practice due to metrology and cost constraints. As the anisotropy is highly correlated with the height of the CNT array and the height can be measured in a much easier and more cost-effective way, we propose a spatial model for predicting the anisotropy using the height. The model takes the spatially distributed two-dimensional (2-D) height as an input and provides a predicted anisotropy distribution in a 2-D space. If the anisotropy measures are obtained, the model can provide a more accurate prediction. The performance of the proposed model is verified by both a simulation study and real data samples. View full abstract»

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  • Safety in Human-Robot Collaborative Manufacturing Environments: Metrics and Control

    Publication Year: 2015 , Page(s): 1 - 12
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2712 KB)  

    New paradigms in industrial robotics no longer require physical separation between robotic manipulators and humans. Moreover, in order to optimize production, humans and robots are expected to collaborate to some extent. In this scenario, involving a shared environment between humans and robots, common motion generation algorithms might turn out to be inadequate for this purpose. View full abstract»

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  • Disturbance Observer-Based Adaptive Tracking Control With Actuator Saturation and Its Application

    Publication Year: 2015 , Page(s): 1 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1854 KB)  

    This paper is concerned with the problem of adaptive tracking control for a class of nonlinear systems with parametric uncertainty, bounded external disturbance, and actuator saturation. In order to achieve robust output tracking for the saturated uncertain nonlinear systems, a combination of adaptive robust control (ARC) and a novel terminal sliding-mode-based nonlinear disturbance observer (TSDO) is proposed, where the modeling inaccuracy and disturbance are integrated as a lumped disturbance. Specifically, the observer errors of estimating the lump disturbances converge to zero in finite-time for improving the precision of estimation. The estimated disturbances are then used in the controller to compensate for the system’s lumped disturbances. The analytical results show that the proposed scheme is stable and can guarantee the asymptotic tracking with the tracking error converging to zero even in the presence of disturbances. Finally, the developed method is illustrated the effectiveness by the application to control of a quarter-car model with active suspension system. View full abstract»

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  • Combining Dynamic Machining Feature With Function Blocks for Adaptive Machining

    Publication Year: 2015 , Page(s): 1 - 14
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2456 KB)  

    Feature-based technologies are widely researched for manufacturing automation. However, in current feature models, features once defined remain constant throughout the whole manufacturing lifecycle. This static feature model is inflexible to support adaptive machining when facing frequent changes to manufacturing resources. This paper presents a new machining feature concept that facilitates responsive changes to the dynamics of machining features in 2.5/3D machining. Basic geometry information for feature construction of complex parts with various intersecting features is represented as a set of meta machining features (MMF). Optimum feature definition is generated adaptively by choosing optimum merging strategies of MMFs according to the capabilities of the selected machine tool, cutter, and cutting parameters. A composite function block for dynamic machining feature modelling is designed with Basic Machining Feature Function Block, Meta Machining Feature Extraction Function Block and Feature Interpreter Function Block. Once changes of the selected machining resources occur, they are informed as input events and machining features are then updated automatically and adaptively based on the event-driven model of function blocks. An example is provided to demonstrate the feasibility and benefits of the developed methodology. View full abstract»

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  • Experiments on Human-in-the-Loop Coordination for Multirobot System With Task Abstraction

    Publication Year: 2015 , Page(s): 1 - 9
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1814 KB)  

    This paper presents the experimental validation of a multiple mobile robot system with human-in-the-loop coordination. It has been proposed that the control framework for networked autonomous robots can be augmented by artificial functions for task abstraction, so that a human operator is able to operate a group of robots remotely. By utilizing the redundancy of a multirobot system with task-space control, the group of mobile robots, in addition to achieving the missions tele-controlled by the human, can perform added tasks simultaneously. In this paper, the human-robot cooperative control system was validated experimentally through a robotic manipulator and a group of mobile robots by taking into account communication delays. Multirobot coverage control, formation control, and cooperative transportation were demonstrated, to validate the performance and efficiency of the robotic control system with human-in-the-loop coordination. View full abstract»

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  • Automated Translational and Rotational Control of Biological Cells With a Robot-Aided Optical Tweezers Manipulation System

    Publication Year: 2015 , Page(s): 1 - 9
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1280 KB)  

    Research and biomedical applications in cell surgery require transportation and rotation of biological cells. In these cell manipulation tasks, the cell of interest must be translated and oriented properly such that the desired component, such as the polar body or other organelles, can be imaged with optical microscopy. This paper presents a holographic optical tweezers (HOT) based system to carry out automated translational control in the plane, and rotational control about one rotational axes of a suspended cell. Based on the proposed general equations of motion of the cell, held in an optical trap, two controllers, one for cell translational and one for rotational control, are developed to translate and orient the cells to the desired position and orientation in a sequential manner. Experiments are performed to demonstrate the effectiveness of the proposed approach. View full abstract»

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  • Modeling, Analysis, and Scheduling of Cluster Tools With Two Independent Arms

    Publication Year: 2015 , Page(s): 1 - 13
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3039 KB)  

    Dual-armed cluster tools for semiconductor manufacturing typically have had two arms fixed in opposite directions. Recently, new cluster tool robot systems with two independent robot arms have been introduced with the expectation that the arms’ flexibility will improve the throughput. However, the productivity gain has yet to be examined. Accordingly, we examine under which circumstances and the extent to which productivity gains can be achieved and how the robot task sequences should be scheduled to maximize the throughput. For this purpose, we develop a Petri net model that represents the tool behavior. We show that the well-known swap sequence, which is known to be optimal for conventional dual-armed tools, is not always optimal. Instead, we identify two other sequences that are optimal under certain conditions. We define the workloads for each process step and the transport module to derive conditions for optimality of the sequences, based on the Petri net model and the workload. We also develop a mixed integer programming (MIP) model to determine optimal sequences among one-cyclic schedules for the cases in which the proposed sequences are not optimal. Furthermore, we analyze and demonstrate how the two independent arms can increase the throughput in comparison to a conventional dual-armed robot. View full abstract»

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  • Early Frame Break Policy for ALOHA-Based RFID Systems

    Publication Year: 2015 , Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1282 KB)  

    Throughput of dynamic frame slotted ALOHA (DFSA) in radio frequency identification (RFID) systems depends on the tags quantity estimate. This paper shows how to apply the slot-by-slot (SbS) estimate approach, along with the policy for the early frame-break. Simulation results show noticeable throughput improvements. View full abstract»

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  • Cooperative Path Following of Multiple Multirotors Over Time-Varying Networks

    Publication Year: 2015 , Page(s): 1 - 13
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2705 KB)  

    This paper addresses the problem of time-coordination of a team of cooperating multirotor unmanned aerial vehicles that exchange information over a supporting time-varying network. A distributed control law is developed to ensure that the vehicles meet the desired temporal assignments of the mission, while flying along predefined collision-free paths, even in the presence of faulty communication networks, temporary link losses, and switching topologies. In this paper, the coordination task is solved by reaching consensus on a suitably defined coordination state. Conditions are derived under which the coordination errors converge to a neighborhood of zero. Simulation and flight test results are presented to validate the theoretical findings. View full abstract»

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  • Collective Motions of Heterogeneous Swarms

    Publication Year: 2015 , Page(s): 1 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1718 KB)  

    The emerging collective motions of swarms of interacting agents are a subject of great interest in application areas ranging from biology to physics and robotics. In this paper, we conduct a careful analysis of the collective dynamics of a swarm of self-propelled heterogeneous, delay-coupled agents. We show the emergence of collective motion patterns and segregation of populations of agents with different dynamic properties; both of these behaviors (pattern formation and segregation) emerge naturally in our model, which is based on self-propulsion and attractive pairwise interactions between agents. We derive the bifurcation structure for emergence of different swarming behaviors in the mean field as a function of physical parameters and verify these results through simulation. View full abstract»

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  • An Automated Force-Controlled Robotic Micromanipulation System for Mechanotransduction Studies of Drosophila Larvae

    Publication Year: 2015 , Page(s): 1 - 9
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1452 KB)  

    The capability of accurately applying millinewton-level touch stimuli to Drosophila larvae and simultaneously observing their resultant fluorescence responses in mechanosensitive neuron transmission will enable novel studies of mechanotransduction neural circuitry. This paper presents an automated robotic micromanipulation system capable of force-controlled mechanical stimulation and quantitative fluorescence imaging of Drosophila larvae, which significantly improves the force regulation accuracy and operation consistency over conventional manual operations. An elastomeric microdevice is developed for efficient immobilization of an array of larvae for subsequent force-controlled touching. A microelectromechanical systems (MEMS) based force sensor is integrated into the robotic system for closed-loop force control of larva touching at a resolution of 50 \mu{\rm N} . Two micromanipulators are coordinately servoed using orchestrated position and force control laws for automatic operations. The system performs simultaneous force-controlled larva touching and fluorescence imaging at a speed of four larvae per minute, with a success rate of 92.5%. This robotic system will greatly facilitate the dissection of mechanotransduction mechanisms of Drosophila larvae at both molecular and cellular levels. View full abstract»

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  • Optimal, Efficient Sequential Control of a Soft-Bodied, Peristaltic Sorting Table

    Publication Year: 2015 , Page(s): 1 - 10
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2695 KB)  

    A peristaltic, soft-bodied xy-sorting table manipulates objects by producing moving wave shapes on its surface. The waves exert forces on the objects which can be used for transportation, reorientation, and local repositioning. The control of such peristaltic robots is mostly unsolved, because important properties of the kinematics, dynamics, and effect of actuation are unknown. Fundamental and practical limitations in measuring the system state lead to numerical difficulties in the form of discontinuous signals in non-Euclidean spaces. View full abstract»

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  • Stereo Vision Based Automated Solder Ball Height and Substrate Coplanarity Inspection

    Publication Year: 2015 , Page(s): 1 - 15
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2766 KB)  

    Solder ball height and substrate coplanarity inspection is essential to the detection of potential connectivity issues in semi-conductor units. Current ball height and substrate coplanarity inspection tools such as laser profiling, fringe projection, and confocal microscopy are expensive, require complicated setup and are slow, which makes them difficult to use in a real-time manufacturing setting. Therefore, a reliable, in-line ball height and substrate coplanarity measurement method is needed for inspecting units undergoing assembly. View full abstract»

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  • Cooperative Control of Multi-Agent Systems With Unknown State-Dependent Controlling Effects

    Publication Year: 2015 , Page(s): 1 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2082 KB)  

    This paper investigates the cooperative control problem of uncertain high-order nonlinear multi-agent systems on directed graph with a fixed topology. Each follower is assumed to have an unknown controlling effect which depends on its own state. By the Nussbaum-type gain technique and the function approximation capability of neural networks, a distributed adaptive neural networks-based controller is designed for each follower in the graph such that all followers can asymptotically synchronize the leader with tracking errors being semi-globally uniform ultimate bounded. Analysis of stability and parameter convergence of the proposed algorithm are conducted based on algebraic graph theory and Lyapunov theory. Finally, a example is provided to validate the theoretical results. View full abstract»

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  • A Timed Petri Nets Model for Performance Evaluation of Intermodal Freight Transport Terminals

    Publication Year: 2015 , Page(s): 1 - 16
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2871 KB)  

    This paper presents a general modeling framework for Intermodal Freight Transport Terminals (IFTTs). The model allows simulating and evaluating the performance of such key elements of the intermodal transportation chain. Hence, it may be used by the decision maker to identify the IFTT bottlenecks, as well as to test different solutions to improve the IFTT dynamics. The proposed modeling framework is modular and based on timed Petri Nets (PNs), where places represent resources and capacities or conditions, transitions model inputs, flows, and activities into the terminal and tokens are intermodal transport units or the means on which they are transported. The model is able to represent the different types of existing IFTTs. Its effectiveness is tested first on an example from the literature and then on a real case study, the railroad inland terminal of a leading Italian intermodal logistics company, showing its ease of application. In the real case study, using the proposed formalism we test the as-is IFTT performance and evaluate alternative possible to-be improvements in order to identify and eliminate emerging criticalities in the terminal dynamics. View full abstract»

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  • Improved Bag of Feature for Automatic Polyp Detection in Wireless Capsule Endoscopy Images

    Publication Year: 2015 , Page(s): 1 - 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (661 KB)  

    Wireless capsule endoscopy (WCE) needs computerized method to reduce the review time for its large image data. In this paper, we propose an improved bag of feature (BoF) method to assist classification of polyps in WCE images. Instead of utilizing a single scale-invariant feature transform (SIFT) feature in the traditional BoF method, we extract different textural features from the neighborhoods of the key points and integrate them together as synthetic descriptors to carry out classification tasks. Specifically, we study influence of the number of visual words, the patch size and different classification methods in terms of classification performance. Comprehensive experimental results reveal that the best classification performance is obtained with the integrated feature strategy using the SIFT and the complete local binary pattern (CLBP) feature, the visual words with a length of 120, the patch size of 8*8, and the support vector machine (SVM). The achieved classification accuracy reaches 93.2%, confirming that the proposed scheme is promising for classification of polyps in WCE images. View full abstract»

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  • Adaptive Iterative Learning Control for High-Speed Trains With Unknown Speed Delays and Input Saturations

    Publication Year: 2015 , Page(s): 1 - 14
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3143 KB)  

    In this paper, an adaptive iterative learning control (AILC) strategy for high-speed trains with unknown speed delays and control input saturations is designed to address speed trajectory tracking problem. The train motion dynamics containing nonlinearities and parametric uncertainties are formulated as a nonlinearly parameterized system. Instead of estimation or modeling of train delays, an unknown time-varying delay term is integrated into the speed on delay analysis by means of Lyapunov–Krasovskii function. Through rigorous analysis, it is confirmed that the proposed AILC mechanism can guarantee L_{[0, T]}^{2} convergence of train speed to the desired profile during operations repeatedly. Case studies with numerical simulations further verify the effectiveness of the proposed approach. View full abstract»

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  • An Efficient and Robust Method for Automatically Identifying the Left Ventricular Boundary in Cine Magnetic Resonance Images

    Publication Year: 2015 , Page(s): 1 - 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1015 KB)  

    Efficient and robust identification of the left ventricular borders remains a challenging problem in cardiology. In this paper, we proposed an automatic method to segment the left ventricles and then identify their borders robustly. The proposed method is named as “ABDC” because it utilizes the strengths of four techniques: Automatic threshold selection; Boundary extraction, Deformation flow tracking, and Convex shape modeling. We compared the proposed method with the PDE optical flow method on 1660 images which are obtained from ten complete short-axis cine MRI datasets (five normal subjects and five patients). As it turned out, the proposed method is more efficient and robust than the benchmark in segmenting LV borders. View full abstract»

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  • Learning to Detect Visual Grasp Affordance

    Publication Year: 2015 , Page(s): 1 - 12
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2160 KB)  

    Appearance-based estimation of grasp affordances is desirable when 3-D scans become unreliable due to clutter or material properties. We develop a general framework for estimating grasp affordances from 2-D sources, including local texture-like measures as well as object-category measures that capture previously learned grasp strategies. Local approaches to estimating grasp positions have been shown to be effective in real-world scenarios, but are unable to impart object-level biases and can be prone to false positives. We describe how global cues can be used to compute continuous pose estimates and corresponding grasp point locations, using a max-margin optimization for category-level continuous pose regression. We provide a novel dataset to evaluate visual grasp affordance estimation; on this dataset we show that a fused method outperforms either local or global methods alone, and that continuous pose estimation improves over discrete output models. Finally, we demonstrate our autonomous object detection and grasping system on the Willow Garage PR2 robot. View full abstract»

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  • Feedback Control of Cluster Tools for Regulating Wafer Delays

    Publication Year: 2015 , Page(s): 1 - 11
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1726 KB)  

    Robotized cluster tools for semiconductor manufacturing have strict time constraints such that a wafer processed at a processing chamber should be unloaded within a specified time limit. Otherwise, it has a serious quality problem due to residual gases and heat within the chamber. Even though there have been studies on identifying a feasible tool operation schedule over such time constraints on wafer delays, such a schedule is subject to timing disruptions or time variation, and thus may violate the time constraints. In this study, we propose a more robust method of regulating wafer delays against timing disruptions not to exceed a specified limit. We first model the discrete-event behavior of a tool by a timed event graph. We then develop a feedback controller for single-armed and dual-armed cluster tools that can satisfy the time constraints by regulating wafer delays. To do this, we develop a feedback controller for the timed event graph by analyzing the timing behavior in a linear system model based on the max-plus algebra. The feedback controller postpones an event or firing of a transition, i.e., loading a wafer into a chamber, until a properly determined time elapses after an associated preceding event occurs. Finally, we present examples of feedback control and show that the feedback control is quite robust even under persistent time variation. View full abstract»

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  • Finite-Time Tracking Control of Rigid Spacecraft Under Actuator Saturations and Faults

    Publication Year: 2015 , Page(s): 1 - 14
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3407 KB)  

    In this paper, an adaptive fast terminal sliding mode control control law (AFTSMCL) is presented to resolve attitude tracking control problem for rigid spacecraft, which can provide finite-time convergence, strong robustness, and fault-tolerant control. Rigorous proof is achieved first. Simulation results are presented to illustrate the effectiveness of presented control law. View full abstract»

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  • Parameterized Distortion-Invariant Feature for Robust Tracking in Omnidirectional Vision

    Publication Year: 2015 , Page(s): 1 - 14
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2255 KB)  

    Central catadioptric omnidirectional images exhibit serious nonlinear distortions due to the involved quadratic mirrors. Therefore, features based on the conventional pin-hole model are hard to achieve satisfactory performances when directly applied to the distorted omnidirectional images. This paper analyzes the catadioptric geometry to facilitate modeling the nonlinear distortions of omnidirectional images. Different to the conventional imaging model, the prior information is considered in catadioptric system. A parameterized neighborhood mapping model is proposed to efficiently calculate the neighborhood of an object based on its measurable radial distance in the image plane. On the basis of the parameterized nonlinear model, a distortion-invariant fragment-based joint-feature mixture model of Gaussian is presented for human target tracking in omnidirectional vision. Under the framework of Gaussian Mixture Model, the problem of feature matching is converted into the feature clustering. The joint probability distribution of a joint-feature class is modeled by a mixture of Gaussian. A weight contribution mechanism is designed to flexibly weight the fragments contribution based on their responses, which leads to a robust tracking even under serious partial occlusion. Finally, experiments validate the advantage of the proposed algorithm over other conventional approaches. View full abstract»

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  • Kinematic Control With Singularity Avoidance for Teaching-Playback Robot Manipulator System

    Publication Year: 2015 , Page(s): 1 - 14
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2062 KB)  

    A teaching-playback robot manipulator system whereby the user controls the manipulator through a teaching pendant has been used widely in industrial applications. Kinematic singularity issue becomes an important problem in the control of robot with a teaching-playback system. In this paper, we propose and investigate three singularity avoidance methods for a teaching-playback robot manipulator system. Nonredundancy singularity avoidance (NRSA) attempts to reduce both the position and orientation errors of the end-effector with the same priority. Redundancy singularity avoidance (RSA) attempts to reduce the position error of the end-effector with the first priority and reduce the orientation error of the end-effector with the second priority; Both NRSA and RSA are based on a modification of a Jacobian matrix. Point-to-point singularity avoidance (PTPSA) makes the end-effector pass through a singular region based on joint-interpolated control without maintaining the position and orientation of the end-effector. Experimental case studies are developed to investigate the manipulator performance when the end-effector approaches the wrist and shoulder singularity. The maximal end-effector trajectory error and users' feelings are statistically evaluated and analyzed in the experiment. The results of the experiment show the effectiveness and practice of the proposed methods. View full abstract»

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  • Adaptive Fuzzy Control of a Class of MIMO Nonlinear System With Actuator Saturation for Greenhouse Climate Control Problem

    Publication Year: 2015 , Page(s): 1 - 17
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3835 KB)  

    This paper presents an indirect adaptive fuzzy control scheme for a class of MIMO non-affine nonlinear systems with unknown dynamics and actuator saturation for greenhouse climate control problems. The objective is to implement output tracking control on nonlinear systems. Using feedback linearization, control inputs with known control gains are first synthesized by well-modeled dynamics of the system, and Taylor series expansion is used to transform unknown non-affine dynamics into the corresponding affine forms. Fuzzy logic systems (FLS) are introduced to estimate the unknown nonlinearity of the transformed affine system and the saturation nonlinearity due to the actuator constraint. The control inputs corresponding to nonlinearity are constructed based on the estimations. By introducing a robust control term, estimation errors and external disturbances are well handled, so as to guarantee the stability when tracking the control process. The control gain estimation obtained by FLS is modified to avoid singularity. Lyapunov stability analysis is performed to derive the adaptive law. To validate the effectiveness of the proposed control scheme, we apply it to a greenhouse climate control problem. The ventilation rate in the greenhouse model is unknown; therefore, it is estimated by FLS. The simulation exhibits satisfactory results, in which the temperature and humidity inside the greenhouse are well tracked. View full abstract»

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T-ASE will publish foundational research on Automation: scientific methods and technologies that improve efficiency, productivity, quality, and reliability, specifically for methods, machines, and systems operating in structured environments over long periods, and the explicit structuring of environments.

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Meet Our Editors

Editor-in-Chief
Ken Goldberg
University of California, Berkeley