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# IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)

Includes the top 50 most frequently accessed documents for this publication according to the usage statistics for the month of

• ### Extreme Learning Machine for Regression and Multiclass Classification

Publication Year: 2012, Page(s):513 - 529
Cited by:  Papers (1075)  |  Patents (2)
| | PDF (1244 KB) | HTML

Due to the simplicity of their implementations, least square support vector machine (LS-SVM) and proximal support vector machine (PSVM) have been widely used in binary classification applications. The conventional LS-SVM and PSVM cannot be used in regression and multiclass classification applications directly, although variants of LS-SVM and PSVM have been proposed to handle such cases. This paper... View full abstract»

• ### An EMG-Based Control for an Upper-Limb Power-Assist Exoskeleton Robot

Publication Year: 2012, Page(s):1064 - 1071
Cited by:  Papers (96)
| | PDF (1224 KB) | HTML

Many kinds of power-assist robots have been developed in order to assist self-rehabilitation and/or daily life motions of physically weak persons. Several kinds of control methods have been proposed to control the power-assist robots according to user's motion intention. In this paper, an electromyogram (EMG)-based impedance control method for an upper-limb power-assist exoskeleton robot is propos... View full abstract»

• ### Multiclass Imbalance Problems: Analysis and Potential Solutions

Publication Year: 2012, Page(s):1119 - 1130
Cited by:  Papers (69)
| | PDF (1096 KB) | HTML

Class imbalance problems have drawn growing interest recently because of their classification difficulty caused by the imbalanced class distributions. In particular, many ensemble methods have been proposed to deal with such imbalance. However, most efforts so far are only focused on two-class imbalance problems. There are unsolved issues in multiclass imbalance problems, which exist in real-world... View full abstract»

• ### Adaptive Particle Swarm Optimization

Publication Year: 2009, Page(s):1362 - 1381
Cited by:  Papers (559)
| | PDF (895 KB) | HTML

An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perform a global search over the entire search space with faster convergence speed. The APSO consists of two main steps. First, by evaluating the population distribution and particle fitness, a real-time evolutionary state est... View full abstract»

• ### An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks

Publication Year: 2004, Page(s):2284 - 2292
Cited by:  Papers (189)
| | PDF (407 KB) | HTML

This work presents a simple sequential growing and pruning algorithm for radial basis function (RBF) networks. The algorithm referred to as growing and pruning (GAP)-RBF uses the concept of "Significance" of a neuron and links it to the learning accuracy. "Significance" of a neuron is defined as its contribution to the network output averaged over all the input data received so far. Using a piecew... View full abstract»

• ### Adaptive Sliding-Mode Control for NonlinearSystems With Uncertain Parameters

Publication Year: 2008, Page(s):534 - 539
Cited by:  Papers (139)
| | PDF (312 KB) | HTML

This correspondence proposes a systematic adaptive sliding- mode controller design for the robust control of nonlinear systems with uncertain parameters. An adaptation tuning approach without high- frequency switching is developed to deal with unknown but bounded system uncertainties. Tracking performance is guaranteed. System robustness, as well as stability, is proven by using the Lyapunov theor... View full abstract»

• ### Exploratory Undersampling for Class-Imbalance Learning

Publication Year: 2009, Page(s):539 - 550
Cited by:  Papers (243)
| | PDF (653 KB) | HTML

Undersampling is a popular method in dealing with class-imbalance problems, which uses only a subset of the majority class and thus is very efficient. The main deficiency is that many majority class examples are ignored. We propose two algorithms to overcome this deficiency. EasyEnsemble samples several subsets from the majority class, trains a learner using each of them, and combines the outputs ... View full abstract»

• ### Ant system: optimization by a colony of cooperating agents

Publication Year: 1996, Page(s):29 - 41
Cited by:  Papers (3872)  |  Patents (20)
| | PDF (1360 KB)

An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discover... View full abstract»

• ### A Self-Learning Particle Swarm Optimizer for Global Optimization Problems

Publication Year: 2012, Page(s):627 - 646
Cited by:  Papers (96)
| | PDF (832 KB) | HTML

Particle swarm optimization (PSO) has been shown as an effective tool for solving global optimization problems. So far, most PSO algorithms use a single learning pattern for all particles, which means that all particles in a swarm use the same strategy. This monotonic learning pattern may cause the lack of intelligence for a particular particle, which makes it unable to deal with different complex... View full abstract»

• ### Second-Order Consensus for Multiagent Systems With Directed Topologies and Nonlinear Dynamics

Publication Year: 2010, Page(s):881 - 891
Cited by:  Papers (377)
| | PDF (319 KB) | HTML

This paper considers a second-order consensus problem for multiagent systems with nonlinear dynamics and directed topologies where each agent is governed by both position and velocity consensus terms with a time-varying asymptotic velocity. To describe the system's ability for reaching consensus, a new concept about the generalized algebraic connectivity is defined for strongly connected networks ... View full abstract»

• ### Reinforcement Learning Versus Model Predictive Control: A Comparison on a Power System Problem

Publication Year: 2009, Page(s):517 - 529
Cited by:  Papers (31)
| | PDF (1038 KB) | HTML

This paper compares reinforcement learning (RL) with model predictive control (MPC) in a unified framework and reports experimental results of their application to the synthesis of a controller for a nonlinear and deterministic electrical power oscillations damping problem. Both families of methods are based on the formulation of the control problem as a discrete-time optimal control problem. The ... View full abstract»

• ### Applications of Artificial Intelligence in Safe Human–Robot Interactions

Publication Year: 2011, Page(s):448 - 459
Cited by:  Papers (12)
| | PDF (1308 KB) | HTML

The integration of industrial robots into the human workspace presents a set of unique challenges. This paper introduces a new sensory system for modeling, tracking, and predicting human motions within a robot workspace. A reactive control scheme to modify a robot's operations for accommodating the presence of the human within the robot workspace is also presented. To this end, a special class of ... View full abstract»

• ### On Learning, Representing, and Generalizing a Task in a Humanoid Robot

Publication Year: 2007, Page(s):286 - 298
Cited by:  Papers (350)
| | PDF (1110 KB) | HTML

We present a programming-by-demonstration framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to different contexts. We validate the architecture through a series of experiments, in which a human demonstrator teaches a humanoid robot simple manipulatory tasks. A probability-based estimation of the relevanc... View full abstract»

• ### Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof

Publication Year: 2008, Page(s):943 - 949
Cited by:  Papers (332)
| | PDF (233 KB) | HTML

Convergence of the value-iteration-based heuristic dynamic programming (HDP) algorithm is proven in the case of general nonlinear systems. That is, it is shown that HDP converges to the optimal control and the optimal value function that solves the Hamilton-Jacobi-Bellman equation appearing in infinite-horizon discrete-time (DT) nonlinear optimal control. It is assumed that, at each iteration, the... View full abstract»

• ### Reinforcement Learning for Partially Observable Dynamic Processes: Adaptive Dynamic Programming Using Measured Output Data

Publication Year: 2011, Page(s):14 - 25
Cited by:  Papers (113)
| | PDF (473 KB) | HTML

Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured inp... View full abstract»

• ### Finite-Time Attitude Tracking Control for Spacecraft Using Terminal Sliding Mode and Chebyshev Neural Network

Publication Year: 2011, Page(s):950 - 963
Cited by:  Papers (115)
| | PDF (360 KB) | HTML

A finite-time attitude tracking control scheme is proposed for spacecraft using terminal sliding mode and Chebyshev neural network (NN) (CNN). The four-parameter representations (quaternion) are used to describe the spacecraft attitude for global representation without singularities. The attitude state (i.e., attitude and velocity) error dynamics is transformed to a double integrator dynamics with... View full abstract»

• ### Human-robot interactions during the robot-assisted urban search and rescue response at the World Trade Center

Publication Year: 2003, Page(s):367 - 385
Cited by:  Papers (280)  |  Patents (1)
| | PDF (2269 KB) | HTML

The World Trade Center (WTC) rescue response provided an unfortunate opportunity to study the human-robot interactions (HRI) during a real unstaged rescue for the first time. A post-hoc analysis was performed on the data collected during the response, which resulted in 17 findings on the impact of the environment and conditions on the HRI: the skills displayed and needed by robots and humans, the ... View full abstract»

• ### Observer-Based Adaptive Fuzzy Backstepping Dynamic Surface Control for a Class of MIMO Nonlinear Systems

Publication Year: 2011, Page(s):1124 - 1135
Cited by:  Papers (156)
| | PDF (293 KB) | HTML

In this paper, an adaptive fuzzy backstepping dynamic surface control (DSC) approach is developed for a class of multiple-input-multiple-output nonlinear systems with immeasurable states. Using fuzzy-logic systems to approximate the unknown nonlinear functions, a fuzzy state observer is designed to estimate the immeasurable states. By combining adaptive-backstepping technique and DSC technique, an... View full abstract»

• ### Optimal Linear-Consensus Algorithms: An LQR Perspective

Publication Year: 2010, Page(s):819 - 830
Cited by:  Papers (85)
| | PDF (307 KB) | HTML

Laplacian matrices play an important role in linear-consensus algorithms. This paper studies optimal linear-consensus algorithms for multivehicle systems with single-integrator dynamics in both continuous-time and discrete-time settings. We propose two global cost functions, namely, interaction-free and interaction-related cost functions. With the interaction-free cost function, we derive the opti... View full abstract»

• ### SVMs Modeling for Highly Imbalanced Classification

Publication Year: 2009, Page(s):281 - 288
Cited by:  Papers (193)
| | PDF (835 KB) | HTML

Traditional classification algorithms can be limited in their performance on highly unbalanced data sets. A popular stream of work for countering the problem of class imbalance has been the application of a sundry of sampling strategies. In this paper, we focus on designing modifications to support vector machines (SVMs) to appropriately tackle the problem of class imbalance. We incorporate differ... View full abstract»

• ### Wrapper–Filter Feature Selection Algorithm Using a Memetic Framework

Publication Year: 2007, Page(s):70 - 76
Cited by:  Papers (158)  |  Patents (1)
| | PDF (532 KB) | HTML

This correspondence presents a novel hybrid wrapper and filter feature selection algorithm for a classification problem using a memetic framework. It incorporates a filter ranking method in the traditional genetic algorithm to improve classification performance and accelerate the search in identifying the core feature subsets. Particularly, the method adds or deletes a feature from a candidate fea... View full abstract»

• ### An approach to online identification of Takagi-Sugeno fuzzy models

Publication Year: 2004, Page(s):484 - 498
Cited by:  Papers (473)  |  Patents (1)
| | PDF (816 KB) | HTML

An approach to the online learning of Takagi-Sugeno (TS) type models is proposed in the paper. It is based on a novel learning algorithm that recursively updates TS model structure and parameters by combining supervised and unsupervised learning. The rule-base and parameters of the TS model continually evolve by adding new rules with more summarization power and by modifying existing rules and par... View full abstract»

• ### Observer-Based Adaptive Fuzzy Backstepping Control for a Class of Stochastic Nonlinear Strict-Feedback Systems

Publication Year: 2011, Page(s):1693 - 1704
Cited by:  Papers (244)
| | PDF (256 KB) | HTML

In this paper, two adaptive fuzzy output feedback control approaches are proposed for a class of uncertain stochastic nonlinear strict-feedback systems without the measurements of the states. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the fuzzy state observer, and by c... View full abstract»

• ### A DSC Approach to Robust Adaptive NN Tracking Control for Strict-Feedback Nonlinear Systems

Publication Year: 2010, Page(s):915 - 927
Cited by:  Papers (208)
| | PDF (799 KB) | HTML

A robust adaptive tracking control approach is presented for a class of strict-feedback single-input-single-output nonlinear systems. By employing radial-basis-function neural networks to account for system uncertainties, the proposed scheme is developed by combining ??dynamic surface control?? and ??minimal learning parameter?? techniques. The key features of the algorithm are that, first, the pr... View full abstract»

• ### Trajectory Tracking Control of Omnidirectional Wheeled Mobile Manipulators: Robust Neural Network-Based Sliding Mode Approach

Publication Year: 2009, Page(s):788 - 799
Cited by:  Papers (51)
| | PDF (442 KB) | HTML

This paper addresses the robust trajectory tracking problem for a redundantly actuated omnidirectional mobile manipulator in the presence of uncertainties and disturbances. The development of control algorithms is based on sliding mode control (SMC) technique. First, a dynamic model is derived based on the practical omnidirectional mobile manipulator system. Then, a SMC scheme, based on the fixed ... View full abstract»

• ### Color Image Segmentation Based on Mean Shift and Normalized Cuts

Publication Year: 2007, Page(s):1382 - 1389
Cited by:  Papers (148)  |  Patents (3)
| | PDF (1001 KB) | HTML

In this correspondence, we develop a novel approach that provides effective and robust segmentation of color images. By incorporating the advantages of the mean shift (MS) segmentation and the normalized cut (Ncut) partitioning methods, the proposed method requires low computational complexity and is therefore very feasible for real-time image segmentation processing. It preprocesses an image by u... View full abstract»

• ### Adaptive NN Backstepping Output-Feedback Control for Stochastic Nonlinear Strict-Feedback Systems With Time-Varying Delays

Publication Year: 2010, Page(s):939 - 950
Cited by:  Papers (189)
| | PDF (282 KB) | HTML

For the first time, this paper addresses the problem of adaptive output-feedback control for a class of uncertain stochastic nonlinear strict-feedback systems with time-varying delays using neural networks (NNs). The circle criterion is applied to designing a nonlinear observer, and no linear growth condition is imposed on nonlinear functions depending on system states. Under the assumption that t... View full abstract»

• ### Development of a biomimetic robotic fish and its control algorithm

Publication Year: 2004, Page(s):1798 - 1810
Cited by:  Papers (198)
| | PDF (542 KB) | HTML

This paper is concerned with the design of a robotic fish and its motion control algorithms. A radio-controlled, four-link biomimetic robotic fish is developed using a flexible posterior body and an oscillating foil as a propeller. The swimming speed of the robotic fish is adjusted by modulating joint's oscillating frequency, and its orientation is tuned by different joint's deflections. Since the... View full abstract»

• ### Evolutionary algorithm based offline/online path planner for UAV navigation

Publication Year: 2003, Page(s):898 - 912
Cited by:  Papers (161)  |  Patents (1)
| | PDF (2343 KB) | HTML

An evolutionary algorithm based framework, a combination of modified breeder genetic algorithms incorporating characteristics of classic genetic algorithms, is utilized to design an offline/online path planner for unmanned aerial vehicles (UAVs) autonomous navigation. The path planner calculates a curved path line with desired characteristics in a three-dimensional (3-D) rough terrain environment,... View full abstract»

• ### Decentralized Robust Adaptive Control for the Multiagent System Consensus Problem Using Neural Networks

Publication Year: 2009, Page(s):636 - 647
Cited by:  Papers (215)
| | PDF (913 KB) | HTML

A robust adaptive control approach is proposed to solve the consensus problem of multiagent systems. Compared with the previous work, the agent's dynamics includes the uncertainties and external disturbances, which is more practical in real-world applications. Due to the approximation capability of neural networks, the uncertain dynamics is compensated by the adaptive neural network scheme. The ef... View full abstract»

• ### Collaborative Control for a Robotic Wheelchair: Evaluation of Performance, Attention, and Workload

Publication Year: 2012, Page(s):876 - 888
Cited by:  Papers (62)
| | PDF (1605 KB) | HTML

Powered wheelchair users often struggle to drive safely and effectively and, in more critical cases, can only get around when accompanied by an assistant. To address these issues, we propose a collaborative control mechanism that assists users as and when they require help. The system uses a multiple-hypothesis method to predict the driver's intentions and, if necessary, adjusts the control signal... View full abstract»

• ### Distributed Adaptive Tracking Control for Synchronization of Unknown Networked Lagrangian Systems

Publication Year: 2011, Page(s):805 - 816
Cited by:  Papers (116)
| | PDF (277 KB) | HTML

This paper investigates the cooperative tracking control problem for a group of Lagrangian vehicle systems with directed communication graph topology. All the vehicles can have different dynamics. A design method for a distributed adaptive protocol is given which guarantees that all the networked systems synchronize to the motion of a target system. The dynamics of the networked systems, as well a... View full abstract»

• ### Identification of nonlinear dynamic systems using functional link artificial neural networks

Publication Year: 1999, Page(s):254 - 262
Cited by:  Papers (176)
| | PDF (300 KB)

We have presented an alternate ANN structure called functional link ANN (FLANN) for nonlinear dynamic system identification using the popular backpropagation algorithm. In contrast to a feedforward ANN structure, i.e., a multilayer perceptron (MLP), the FLANN is basically a single layer structure in which nonlinearity is introduced by enhancing the input pattern with nonlinear functional expansion... View full abstract»

• ### A hybrid of genetic algorithm and particle swarm optimization for recurrent network design

Publication Year: 2004, Page(s):997 - 1006
Cited by:  Papers (411)  |  Patents (2)
| | PDF (472 KB) | HTML

An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid of genetic algorithm (GA) and particle swarm optimization (PSO), and is thus called HGAPSO. In HGAPSO, individuals in a new generation are created, not only by crossover a... View full abstract»

• ### Stability Analysis for Linear Switched Systems With Time-Varying Delay

Publication Year: 2008, Page(s):528 - 533
Cited by:  Papers (133)
| | PDF (143 KB) | HTML

This correspondence considers the stability problem for a class of linear switched systems with time-varying delay in the sense of Hurwitz convex combination. The bound of derivative of the time-varying delay can be an unknown constant. It is concluded that the stability result for linear switched systems still holds for such systems with time-varying delay under a certain delay bound. Moreover, t... View full abstract»

• ### Genetic K-means algorithm

Publication Year: 1999, Page(s):433 - 439
Cited by:  Papers (344)
| | PDF (180 KB)

In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal partition of a given data into a specified number of clusters. GA's used earlier in clustering employ either an expensive crossover operator to generate valid child chromosomes from parent chromosomes or a costly fitness function or both. To circumvent these expensive operations, we hybridize GA with a cl... View full abstract»

• ### An Adaptive Differential Evolution Algorithm With Novel Mutation and Crossover Strategies for Global Numerical Optimization

Publication Year: 2012, Page(s):482 - 500
Cited by:  Papers (167)
| | PDF (1503 KB) | HTML

Differential evolution (DE) is one of the most powerful stochastic real parameter optimizers of current interest. In this paper, we propose a new mutation strategy, a fitness- induced parent selection scheme for the binomial crossover of DE, and a simple but effective scheme of adapting two of its most important control parameters with an objective of achieving improved performance. The new mutati... View full abstract»

• ### Cooperative Output Regulation With Application to Multi-Agent Consensus Under Switching Network

Publication Year: 2012, Page(s):864 - 875
Cited by:  Papers (97)
| | PDF (1023 KB) | HTML

In this paper, we consider the cooperative output regulation of linear multi-agent systems under switching network. The problem can be viewed as a generalization of the leader-following consensus problem of multi-agent systems. Due to the limited information exchanges of different subsystems, the problem cannot be solved by the decentralized approach and is not allowed to be solved by the centrali... View full abstract»

• ### Robust $H_{infty}$ Control for Networked Systems With Random Packet Losses

Publication Year: 2007, Page(s):916 - 924
Cited by:  Papers (264)
| | PDF (301 KB) | HTML

In this paper, the robust Hinfin control problem Is considered for a class of networked systems with random communication packet losses. Because of the limited bandwidth of the channels, such random packet losses could occur, simultaneously, in the communication channels from the sensor to the controller and from the controller to the actuator. The random packet loss is assumed to obey the Bernoul... View full abstract»

• ### Robust Fault Detection for Switched Linear Systems With State Delays

Publication Year: 2009, Page(s):800 - 805
Cited by:  Papers (140)
| | PDF (279 KB) | HTML

This correspondence deals with the problem of robust fault detection for discrete-time switched systems with state delays under an arbitrary switching signal. The fault detection filter is used as the residual generator, in which the filter parameters are dependent on the system mode. Attention is focused on designing the robust fault detection filter such that, for unknown inputs, control inputs,... View full abstract»

• ### Dynamics of facial expression: recognition of facial actions and their temporal segments from face profile image sequences

Publication Year: 2006, Page(s):433 - 449
Cited by:  Papers (201)
| | PDF (4689 KB) | HTML

Automatic analysis of human facial expression is a challenging problem with many applications. Most of the existing automated systems for facial expression analysis attempt to recognize a few prototypic emotional expressions, such as anger and happiness. Instead of representing another approach to machine analysis of prototypic facial expressions of emotion, the method presented in this paper atte... View full abstract»

• ### Adaptive Fuzzy Output-Feedback Controller Design for Nonlinear Time-Delay Systems With Unknown Control Direction

Publication Year: 2009, Page(s):363 - 374
Cited by:  Papers (120)
| | PDF (243 KB) | HTML

In this paper, the robust-control problem is investigated for a class of uncertain nonlinear time-delay systems via dynamic output-feedback approach. The considered system is in the strict-feedback form with unknown control direction. A full-order observer is constructed with the gains computed via linear matrix inequality at first. Then, with the bounds of uncertain functions known, we design the... View full abstract»

• ### Fuzzy State/Disturbance Observer Design for T–S Fuzzy Systems With Application to Sensor Fault Estimation

Publication Year: 2008, Page(s):875 - 880
Cited by:  Papers (69)
| | PDF (404 KB) | HTML

A novel fuzzy-observer-design approach is presented for Takagi-Sugeno fuzzy models with unknown output disturbances. In order to decouple the unknown output disturbance, an augmented fuzzy descriptor model is constructed by supposing the disturbance to be an auxiliary state vector. A fuzzy state-space observer is next designed for the augmented fuzzy descriptor system, and the simultaneous estimat... View full abstract»

• ### Sensible Organizations: Technology and Methodology for Automatically Measuring Organizational Behavior

Publication Year: 2009, Page(s):43 - 55
Cited by:  Papers (96)  |  Patents (5)
| | PDF (617 KB) | HTML

We present the design, implementation, and deployment of a wearable computing platform for measuring and analyzing human behavior in organizational settings. We propose the use of wearable electronic badges capable of automatically measuring the amount of face-to-face interaction, conversational time, physical proximity to other people, and physical activity levels in order to capture individual a... View full abstract»

• ### Rendezvous-Guidance Trajectory Planning for Robotic Dynamic Obstacle Avoidance and Interception

Publication Year: 2006, Page(s):1432 - 1441
Cited by:  Papers (13)
| | PDF (1197 KB) | HTML

This correspondence presents a novel online trajectory-planning method for the autonomous robotic interception of moving targets in the presence of dynamic obstacles, i.e., position and velocity matching (also referred to as rendezvous). The proposed time-optimal interception method is a hybrid algorithm that augments a novel rendezvous-guidance (RG) technique with the velocity-obstacle approach, ... View full abstract»

• ### Distributed Primal–Dual Subgradient Method for Multiagent Optimization via Consensus Algorithms

Publication Year: 2011, Page(s):1715 - 1724
Cited by:  Papers (56)
| | PDF (230 KB) | HTML

This paper studies the problem of optimizing the sum of multiple agents' local convex objective functions, subject to global convex inequality constraints and a convex state constraint set over a network. Through characterizing the primal and dual optimal solutions as the saddle points of the Lagrangian function associated with the problem, we propose a distributed algorithm, named the distributed... View full abstract»

• ### Multisensor-Based Human Detection and Tracking for Mobile Service Robots

Publication Year: 2009, Page(s):167 - 181
Cited by:  Papers (115)
| | PDF (1496 KB) | HTML Media

One of fundamental issues for service robots is human-robot interaction. In order to perform such a task and provide the desired services, these robots need to detect and track people in the surroundings. In this paper, we propose a solution for human tracking with a mobile robot that implements multisensor data fusion techniques. The system utilizes a new algorithm for laser-based leg detection u... View full abstract»

• ### A New Evolutionary Algorithm for Solving Many-Objective Optimization Problems

Publication Year: 2008, Page(s):1402 - 1412
Cited by:  Papers (75)
| | PDF (1358 KB) | HTML

In this paper, we focus on the study of evolutionary algorithms for solving multiobjective optimization problems with a large number of objectives. First, a comparative study of a newly developed dynamical multiobjective evolutionary algorithm (DMOEA) and some modern algorithms, such as the indicator-based evolutionary algorithm, multiple single objective Pareto sampling, and nondominated sorting ... View full abstract»

Publication Year: 2011, Page(s):173 - 182
Cited by:  Papers (10)
| | PDF (755 KB) | HTML

Due to the importance of high-quality customer service, many companies use intelligent helpdesk systems (e.g., case-based systems) to improve customer service quality. However, these systems face two challenges: 1) Case retrieval measures: most case-based systems use traditional keyword-matching-based ranking schemes for case retrieval and have difficulty to capture the semantic meanings of cases ... View full abstract»

• ### Tracking Control of a Closed-Chain Five-Bar Robot With Two Degrees of Freedom by Integration of an Approximation-Based Approach and Mechanical Design

Publication Year: 2012, Page(s):1470 - 1479
Cited by:  Papers (20)
| | PDF (770 KB) | HTML

The trajectory tracking problem of a closed-chain five-bar robot is studied in this paper. Based on an error transformation function and the backstepping technique, an approximation-based tracking algorithm is proposed, which can guarantee the control performance of the robotic system in both the stable and transient phases. In particular, the overshoot, settling time, and final tracking error of ... View full abstract»

## Aims & Scope

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics focuses on cybernetics, including communication and control across humans, machines and organizations at the structural or neural level

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Cybernetics.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Dr. Eugene Santos, Jr.
Thayer School of Engineering
Dartmouth College