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Robotics, IEEE Transactions on

Issue 6 • Date Dec. 2008

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Displaying Results 1 - 25 of 26
  • Table of contents

    Page(s): C1 - C 1
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  • IEEE Transactions on Robotics publication information

    Page(s): C2
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    Freely Available from IEEE
  • Editorial

    Page(s): 1261
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    Freely Available from IEEE
  • Mechanics Modeling of Tendon-Driven Continuum Manipulators

    Page(s): 1262 - 1273
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (533 KB) |  | HTML iconHTML  

    Continuum robotic manipulators articulate due to their inherent compliance. Tendon actuation leads to compression of the manipulator, extension of the actuators, and is limited by the practical constraint that tendons cannot support compression. In light of these observations, we present a new linear model for transforming desired beam configuration to tendon displacements and vice versa. We begin from first principles in solid mechanics by analyzing the effects of geometrically nonlinear tendon loads. These loads act both distally at the termination point and proximally along the conduit contact interface. The resulting model simplifies to a linear system including only the bending and axial modes of the manipulator as well as the actuator compliance. The model is then manipulated to form a concise mapping from beam configuration-space parameters to n redundant tendon displacements via the internal loads and strains experienced by the system. We demonstrate the utility of this model by implementing an optimal feasible controller. The controller regulates axial strain to a constant value while guaranteeing positive tendon forces and minimizing their magnitudes over a range of articulations. The mechanics-based model from this study provides insight as well as performance gains for this increasingly ubiquitous class of manipulators. View full abstract»

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  • Fast Dynamics of an Eel-Like Robot—Comparisons With Navier–Stokes Simulations

    Page(s): 1274 - 1288
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1216 KB) |  | HTML iconHTML  

    This paper proposes a dynamic model of the swim of elongated fish suited to the online control of biomimetic eel-like robots. The approach can be considered as an extension of the original reactive ldquolarge elongated body theoryrdquo of Lighthill to the 3-D self-propulsion to which a resistive empirical model has been added. While all the mathematical fundamentals have been detailed by Boyer . (http://www.irccyn.ec-nantes.fr/hebergement/Publications/2007/3721.pdf, 2007), this paper essentially focuses on the numerical validation and calibration of the model and the study of swimming gaits. The proposed model is coupled to an algorithm allowing us to compute the motion of the fish head and the field of internal control torque from the knowledge of the imposed internal strain fields. Based on the Newton-Euler formalism of robot dynamics, this algorithm works faster than real time. As far as precision is concerned, many tests obtained with several planar and 3-D gaits are reported and compared (in the planar case) with a Navier-Stokes solver, which, until today have been devoted to the planar swim. The comparisons obtained are very encouraging since in all the cases we tested, the differences between our simplified and reference simulations do not exceed 10%. View full abstract»

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  • Energy-Efficient and High-Speed Dynamic Biped Locomotion Based on Principle of Parametric Excitation

    Page(s): 1289 - 1301
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (599 KB) |  | HTML iconHTML  

    We clarified that the common necessary condition for generating a dynamic gait results from the requirement to restore mechanical energy through studies on passive dynamic walking mechanisms. This paper proposes a novel method of generating a dynamic gait that can be found in the mechanism of a swing inspired by the principle of parametric excitation using telescopic leg actuation. We first introduce a simple underactuated biped model with telescopic legs and semicircular feet and propose a law to control the telescopic leg motion. We found that a high-speed dynamic bipedal gait can easily be generated by only pumping the swing leg mass. We then conducted parametric studies by adjusting the control and physical parameters and determined how well the basic gait performed by introducing some performance indexes. Improvements in energy efficiency by using an elastic-element effect were also numerically investigated. Further, we theoretically proved that semicircular feet have a mechanism that decreases the energy dissipated by heel-strike collisions. We provide insights throughout this paper into how zero-moment-point-free robots can generate a novel biped gait. View full abstract»

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  • Design and Quasi-Static Locomotion Analysis of the Rolling Disk Biped Hybrid Robot

    Page(s): 1302 - 1314
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (906 KB) |  | HTML iconHTML  

    Motivated by the need for greater speed, efficiency, and adaptability in climbing and walking robots, we have developed a bipedal planar robot that complements its walking and climbing capabilities with rolling. Rolling capabilities are provided by an innovative morphology, without the need for additional resources beyond those required by walking and climbing. Herein, we present the design of this robot, the development of a quasi-static rolling controller, and a comparison of experimentally obtained speed and energy data for walking versus rolling locomotion. We show that rolling can significantly improve energy efficiency over walking-as much as a factor of 5.5. We also demonstrate the ability to roll up slopes and roll over obstacles. View full abstract»

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  • Advanced Programmed Motion Tracking Control of Nonholonomic Mechanical Systems

    Page(s): 1315 - 1328
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (521 KB) |  | HTML iconHTML  

    Trajectory tracking control of nonholonomic systems has been extended to tracking a desired motion. The desired motion is specified by equations of constraints, referred to as programmed, which may be differential equations of high order and may be nonholonomic. The strategy enables motion tracking control under the assumption that the system dynamics are accurately known. It is referred to as a model reference tracking control strategy for programmed motion. In this paper, adaptive and repetitive extensions of the strategy are proposed. Two selected advanced tracking control algorithms, i.e., the desired compensation adaptation law and the repetitive control law, which were originally dedicated to holonomic systems, are adapted to motion tracking control of nonholonomic systems. Simulation studies that illustrate programmed motion tracking control of systems with unknown parameters and the performance of repetitive motions are provided. A new performance measure to evaluate a programmed motion tracking performance is introduced. View full abstract»

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  • A Natural Feature Representation for Unstructured Environments

    Page(s): 1329 - 1340
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1267 KB) |  | HTML iconHTML  

    This paper addresses the long-standing problem of feature representation in the natural world for autonomous navigation systems. The proposed representation combines Isomap, which is a nonlinear manifold learning algorithm, with expectation maximization, which is a statistical learning scheme. The representation is computed off-line and results in a compact, nonlinear, non-Gaussian sensor likelihood model. This model can be easily integrated into estimation algorithms for navigation and tracking. The compactness of the model makes it especially attractive for deployment in decentralized sensor networks. Real sensory data from unstructured terrestrial and underwater environments are used to demonstrate the versatility of the computed likelihood model. The experimental results show that this approach can provide consistent models of natural environments to facilitate complex visual tracking and data-association problems. View full abstract»

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  • Gaussian Process Models for Indoor and Outdoor Sensor-Centric Robot Localization

    Page(s): 1341 - 1351
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1589 KB) |  | HTML iconHTML  

    This paper presents an approach to building a map from a sparse set of noisy observations, taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process (GP) framework. The approach is validated experimentally both in an indoor office environment and an outdoor urban environment, using observations from an omnidirectional camera mounted on a mobile robot. A set of training data is collected from each environment and processed offline to produce a GP model. The robot then uses that model to localize while traversing each environment. View full abstract»

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  • Efficient Homography-Based Tracking and 3-D Reconstruction for Single-Viewpoint Sensors

    Page(s): 1352 - 1364
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (938 KB) |  | HTML iconHTML  

    This paper addresses the problem of motion estimation and 3-D reconstruction through visual tracking with a single-viewpoint sensor and, in particular, how to generalize tracking to calibrated omnidirectional cameras. We analyze different minimization approaches for the intensity-based cost function (sum of squared differences). In particular, we propose novel variants of the efficient second-order minimization (ESM) with better computational complexities and compare these algorithms with the inverse composition (IC) and the hyperplane approximation (HA). Issues regarding the use of the IC and HA for 3-D tracking are discussed. We show that even though an iteration of ESM is computationally more expensive than an iteration of IC, the faster convergence rate makes it globally faster. The tracking algorithm was validated by using an omnidirectional sensor mounted on a mobile robot. View full abstract»

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  • iSAM: Incremental Smoothing and Mapping

    Page(s): 1365 - 1378
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1096 KB) |  | HTML iconHTML  

    In this paper, we present incremental smoothing and mapping (iSAM), which is a novel approach to the simultaneous localization and mapping problem that is based on fast incremental matrix factorization. iSAM provides an efficient and exact solution by updating a QR factorization of the naturally sparse smoothing information matrix, thereby recalculating only those matrix entries that actually change. iSAM is efficient even for robot trajectories with many loops as it avoids unnecessary fill-in in the factor matrix by periodic variable reordering. Also, to enable data association in real time, we provide efficient algorithms to access the estimation uncertainties of interest based on the factored information matrix. We systematically evaluate the different components of iSAM as well as the overall algorithm using various simulated and real-world datasets for both landmark and pose-only settings. View full abstract»

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  • Robot-to-Robot Relative Pose Estimation From Range Measurements

    Page(s): 1379 - 1393
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (915 KB) |  | HTML iconHTML  

    In this paper, we address the problem of determining the 2-D relative pose of pairs of communicating robots from (1) robot-to-robot distance measurements and (2) displacement estimates expressed in each robot's reference frame. Specifically, we prove that for nonsingular configurations, the minimum number of distance measurements required for determining all six possible solutions for the 3 degree-of-freedom (3-DOF) robot-to-robot transformation is 3. Additionally, we show that given four distance measurements, the maximum number of solutions is 4, while five distance measurements are sufficient for uniquely determining the robot-to-robot transformation. Furthermore, we present an efficient algorithm for computing the unique solution in closed form and describe an iterative least-squares process for improving its accuracy. Finally, we derive necessary and sufficient observability conditions based on Lie derivatives and evaluate the performance of the proposed estimation algorithms both in simulation and via experiments. View full abstract»

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  • Decentralized Perimeter Surveillance Using a Team of UAVs

    Page(s): 1394 - 1404
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (945 KB) |  | HTML iconHTML  

    This paper poses the cooperative perimeter-surveillance problem and offers a decentralized solution that accounts for perimeter growth (expanding or contracting) and insertion/deletion of team members. By identifying and sharing the critical coordination information and by exploiting the known communication topology, only a small communication range is required for accurate performance. Simulation and hardware results are presented that demonstrate the applicability of the solution. View full abstract»

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  • Convergence-Preserving Switching for Topology-Dependent Decentralized Systems

    Page(s): 1405 - 1415
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (617 KB) |  | HTML iconHTML  

    Stability analysis of decentralized control mechanisms for networked coordinating systems has generally focused on specific controller implementations, such as nearest-neighbor and other types of proximity graph control laws. This approach often misses the need for the addition of other control structures to improve global characteristics of the network. An example of such a situation is the use of a Gabriel graph, which is essentially a nearest-neighbor rule modified to ensure global connectivity of the network if the agents are pairwise connected through their sensor inputs. We present a method of ensuring provable stability of decentralized switching systems by employing a hysteresis rule that uses a zero-sum consensus algorithm. We demonstrate the application of this result to several special cases, including nearest-neighbor control laws, Gabriel graph rules, diffuse target tracking, and hierarchical heterogeneous systems. View full abstract»

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  • Distributed Connectivity Control of Mobile Networks

    Page(s): 1416 - 1428
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (862 KB) |  | HTML iconHTML  

    Control of mobile networks raises fundamental and novel problems in controlling the structure of the resulting dynamic graphs. In particular, in applications involving mobile sensor networks and multiagent systems, a great new challenge is the development of distributed motion algorithms that guarantee connectivity of the overall network. Motivated by the inherently discrete nature of graphs as combinatorial objects, we address this challenge using a key control decomposition. First, connectivity control of the network structure is performed in the discrete space of graphs and relies on local estimates of the network topology used, along with algebraic graph theory, to verify link deletions with respect to connectivity. Tie breaking, when multiple such link deletions can violate connectivity, is achieved by means of gossip algorithms and distributed market-based control. Second, motion control is performed in the continuous configuration space, where nearest-neighbor potential fields are used to maintain existing links in the network. Integration of the earlier controllers results in a distributed, multiagent, hybrid system, for which we show that the resulting motion always ensures connectivity of the network, while it reconfigures toward certain secondary objectives. Our approach can also account for communication time delays as well as collision avoidance and is illustrated in nontrivial computer simulations. View full abstract»

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  • On Discrete-Time Pursuit-Evasion Games With Sensing Limitations

    Page(s): 1429 - 1439
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (335 KB) |  | HTML iconHTML  

    In this paper, we address discrete-time pursuit-evasion games in the plane where every player has identical sensing and motion ranges restricted to closed disks of given sensing and stepping radii. A single evader is initially located inside a bounded subset of the environment and does not move until detected. We propose a sweep-pursuit-capture pursuer strategy to capture the evader and apply it to two variants of the game. The first involves a single pursuer and an evader in a bounded convex environment, and the second involves multiple pursuers and an evader in a boundaryless environment. In the first game, we give a sufficient condition on the ratio of sensing to stepping radius of the players that guarantees capture. In the second, we determine the minimum probability of capture, which is a function of a novel pursuer formation and independent of the initial evader location. The sweep and pursuit phases reduce both games to previously studied problems with unlimited range sensing, and capture is achieved using available strategies. We obtain novel upper bounds on the capture time and present simulation studies that address the performance of the strategies under sensing errors, different ratios of sensing to stepping radius, greater evader speed, and a different number of pursuers. View full abstract»

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  • Optimal Extended Jacobian Inverse Kinematics Algorithms for Robotic Manipulators

    Page(s): 1440 - 1445
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (249 KB) |  | HTML iconHTML  

    Extended Jacobian inverse kinematics algorithms for redundant robotic manipulators are defined by combining the manipulator's kinematics with an augmenting kinematics map in such a way that the combination becomes a local diffeomorphism of the augmented taskspace. A specific choice of the augmentation relies on the optimal approximation by the extended Jacobian of the Jacobian pseudoinverse (the Moore-Penrose inverse of the Jacobian). In this paper, we propose a novel formulation of the approximation problem, rooted conceptually in the Riemannian geometry. The resulting optimality conditions assume the form of a Poisson equation involving the Laplace-Beltrami operator. Two computational examples illustrate the theory. View full abstract»

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  • Differentially Flat Designs of Underactuated Open-Chain Planar Robots

    Page(s): 1445 - 1451
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (468 KB) |  | HTML iconHTML  

    A fully actuated system can execute any joint trajectory. However, if the system is underactuated, not all joint trajectories are attainable. For such systems, it is difficult to characterize attainable joint trajectories analytically. Numerical methods are generally used to characterize these. This paper investigates the property of differential flatness for underactuated planar open-chain robots and studies dependence on inertia distribution within the system. It is shown that certain choices of inertia distributions make an underactuated open-chain planar robot with revolute joints feedback linearizable, i.e., also differentially flat. Once this property is established, trajectory between any two points in the state space can be planned, and a controller can be developed to correct for errors. To demonstrate the proposed methodology in hardware, experiments with an underactuated 3-DOF planar robot are also presented. View full abstract»

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  • CBUG: A Quadratically Competitive Mobile Robot Navigation Algorithm

    Page(s): 1451 - 1457
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (397 KB) |  | HTML iconHTML  

    This paper is concerned with online navigation of a size D mobile robot in an unknown planar environment. A formal means for assessing algorithms for online tasks is competitiveness. For the navigation task, competitiveness measures the algorithm's path length relative to the optimal offline path length. While competitiveness usually means constant relative performance, it is measured in this paper in terms of a quadratic relationship between online performance and optimal offline solution. An online navigation algorithm for a size D robot called CBUG is described. The competitiveness of CBUG is analyzed and shown to be quadratic in the length of the shortest offline path. Moreover, it is shown that, in general, quadratic competitiveness is the best achievable performance over all online navigation algorithms. Thus, up to constants, CBUG achieves optimal competitiveness. The algorithm is improved with some practical speedups, and the usefulness of its competitiveness in terms of path stability is illustrated in office-like environments. View full abstract»

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  • Observer-Based Leader-Following Formation Control Using Onboard Sensor Information

    Page(s): 1457 - 1462
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (647 KB) |  | HTML iconHTML  

    In this paper, leader-following formation control for mobile multiagent systems with limited sensor information is studied. The control algorithms developed require information available from onboard sensors only, and in particular, the measurement of the leader (neighbor) speed is not needed. Instead, an observer is designed for the estimation of this speed. With the proposed control algorithms as building blocks, many complex formations can be obtained. View full abstract»

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  • Dynamical System Modulation for Robot Learning via Kinesthetic Demonstrations

    Page(s): 1463 - 1467
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (587 KB) |  | HTML iconHTML  

    We present a system for robust robot skill acquisition from kinesthetic demonstrations. This system allows a robot to learn a simple goal-directed gesture and correctly reproduce it despite changes in the initial conditions and perturbations in the environment. It combines a dynamical system control approach with tools of statistical learning theory and provides a solution to the inverse kinematics problem when dealing with a redundant manipulator. The system is validated on two experiments involving a humanoid robot: putting an object into a box and reaching for and grasping an object. View full abstract»

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  • List of Reviewers

    Page(s): 1468 - 1472
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (42 KB)  

    Lists, in alphabetical order, the reviewers who contributed to the IEEE Transactions on Robotics between October 1, 2007 and September 30, 2008. View full abstract»

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  • 2008 Index IEEE Transactions on Robotics Vol. 24

    Page(s): 1473 - 1488
    Save to Project icon | Request Permissions | PDF file iconPDF (174 KB)  
    Freely Available from IEEE
  • IEEE Robotics and Automation Society Information

    Page(s): C3
    Save to Project icon | Request Permissions | PDF file iconPDF (34 KB)  
    Freely Available from IEEE

Aims & Scope

IEEE Transactions on Robotics covers both theory and applications on topics including: kinematics, dynamics, control, and simulation of robots and intelligent machines and systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Frank Park
Seoul National University