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Robotics, IEEE Transactions on

Issue 6 • Date Dec. 2011

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Displaying Results 1 - 20 of 20
  • Table of contents

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

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  • Statics and Dynamics of Continuum Robots With General Tendon Routing and External Loading

    Page(s): 1033 - 1044
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1036 KB) |  | HTML iconHTML  

    Tendons are a widely used actuation strategy for continuum robots that enable forces and moments to be transmitted along the robot from base-mounted actuators. Most prior robots have used tendons routed in straight paths along the robot. However, routing tendons through general curved paths within the robot offers potential advantages in reshaping the workspace and enabling a single section of the robot to achieve a wider variety of desired shapes. In this paper, we provide a new model for the statics and dynamics of robots with general tendon routing paths that is derived by coupling the classical Cosserat-rod and Cosserat-string models. This model also accounts for general external loading conditions and includes traditional axially routed tendons as a special case. The advantage of the usage of this coupled model for straight-tendon robots is that it accounts for the distributed wrenches that tendons apply along the robot. We show that these are necessary to consider when the robot is subjected to out-of-plane external loads. Our experimental results demonstrate that the coupled model matches experimental tip positions with an error of 1.7% of the robot length, in a set of experiments that include both straight and nonstraight routing cases, with both point and distributed external loads. View full abstract»

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  • Position Control of Motion Compensation Cardiac Catheters

    Page(s): 1045 - 1055
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (708 KB) |  | HTML iconHTML  

    Robotic catheters have the potential to revolutionize cardiac surgery by enabling minimally invasive structural repairs within the beating heart. This paper presents an actuated catheter system that compensates for the fast motion of cardiac tissue using 3-D ultrasound image guidance. We describe the design and operation of the mechanical drive system and catheter module and analyze the catheter performance limitations of friction and backlash in detail. To mitigate these limitations, we propose and evaluate mechanical and control-system compensation methods, which include inverse and model-based backlash compensation, to improve the system performance. Finally, in vivo results are presented, which demonstrate that the catheter can track the cardiac tissue motion with less than 1-mm rms error. The ultimate goal of this research is to create a fast and dexterous robotic catheter system that can perform surgery on the delicate structures inside of the beating heart. View full abstract»

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  • Stable Precision Grasps by Underactuated Grippers

    Page(s): 1056 - 1066
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (822 KB) |  | HTML iconHTML  

    The ability of underactuated hands to grasp small objects is very limited, because the precision grasp is normally unstable. The goal of this paper is to achieve stable precision grasps by means of simple design modifications of the distal phalanges of the fingers. These modifications comprise the curving of the contact area of the distal phalanx, the application of a mechanical limit to prevent hyperextension of the distal phalanx, and the application of a compliant joint between the proximal and distal phalanges. A model is developed to calculate the limits of the finger dimensions in order to achieve stable precision grasps for different object sizes. An experimental setup is used to test the grasp stability and to verify the calculated results. It is concluded that stable precision grasps exist for the combination of concavely curved distal phalanges with a mechanical limit or with a compliant joint, if the limits to the finger dimensions are satisfied. View full abstract»

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  • Human-Inspired Robotic Grasp Control With Tactile Sensing

    Page(s): 1067 - 1079
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (920 KB) |  | HTML iconHTML  

    We present a novel robotic grasp controller that allows a sensorized parallel jaw gripper to gently pick up and set down unknown objects once a grasp location has been selected. Our approach is inspired by the control scheme that humans employ for such actions, which is known to centrally depend on tactile sensation rather than vision or proprioception. Our controller processes measurements from the gripper's fingertip pressure arrays and hand-mounted accelerometer in real time to generate robotic tactile signals that are designed to mimic human SA-I, FA-I, and FA-II channels. These signals are combined into tactile event cues that drive the transitions between six discrete states in the grasp controller: Close, Load, Lift and Hold, Replace, Unload, and Open. The controller selects an appropriate initial grasping force, detects when an object is slipping from the grasp, increases the grasp force as needed, and judges when to release an object to set it down. We demonstrate the promise of our approach through implementation on the PR2 robotic platform, including grasp testing on a large number of real-world objects. View full abstract»

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  • Chance-Constrained Optimal Path Planning With Obstacles

    Page(s): 1080 - 1094
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    Autonomous vehicles need to plan trajectories to a specified goal that avoid obstacles. For robust execution, we must take into account uncertainty, which arises due to uncertain localization, modeling errors, and disturbances. Prior work handled the case of set-bounded uncertainty. We present here a chance-constrained approach, which uses instead a probabilistic representation of uncertainty. The new approach plans the future probabilistic distribution of the vehicle state so that the probability of failure is below a specified threshold. Failure occurs when the vehicle collides with an obstacle or leaves an operator-specified region. The key idea behind the approach is to use bounds on the probability of collision to show that, for linear-Gaussian systems, we can approximate the nonconvex chance-constrained optimization problem as a disjunctive convex program. This can be solved to global optimality using branch-and-bound techniques. In order to improve computation time, we introduce a customized solution method that returns almost-optimal solutions along with a hard bound on the level of suboptimality. We present an empirical validation with an aircraft obstacle avoidance example. View full abstract»

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  • Planning and Fast Replanning Safe Motions for Humanoid Robots

    Page(s): 1095 - 1106
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    This paper introduces effective numerical methods for the planning and fast replanning of safe motions to ensure the safety, balance, and integrity of humanoid robots over the whole motion duration. Our safe methods do not depend on, nor are connected to, any type of modeling or constraints. To plan safe motions, certain constraints have to be satisfied over a continuous interval of time. Classical methods revert to time-grid discretization, which can be risky for the robot. We introduce a hybrid method to plan safe motions, which combines a classical unsafe method with a verification step that checks constraint violation and computes excess by the usage of interval analysis. When the robot meets unexpected situations, it has to replan a new motion, which is often too time consuming. Hence, we introduce a new method to rapidly replan safe motions, i.e., in less than 2 s CPU time. It computes offline feasible subsets in the vicinity of safe motions and finds online a solution in these subsets without actually recomputing the nonlinear constraints. Our methods are validated by the use the HOAP-3 robot, where the motions are run with no balance controller. View full abstract»

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  • Climbing Strategy for a Flexible Tree Climbing Robot—Treebot

    Page(s): 1107 - 1117
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (924 KB) |  | HTML iconHTML  

    In this paper, we propose an autonomous tree climbing strategy for a novel tree climbing robot that is named Treebot. The proposed algorithm aims to guide Treebot in climbing along an optimal path by the use of minimal sensing resources. Inspired by inchworms, the algorithm reconstructs the shape of a tree simply by the use of tactile sensors. It reveals how the realization of an environment can be achieved with limited tactile information. An efficient nonholonomic motion planning strategy is also proposed to make Treebot climb on an optimal path. This is accomplished by the prediction of the future shape of the tree. The study that is presented in this paper also includes the formulation of Treebot kinematics and an analysis of the workspace of Treebot on different shapes of a tree. Numerous experiments have been conducted to evaluate the proposed autonomous climbing algorithm and to unveil the ability of Treebot. View full abstract»

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  • Mobile Sensor Network Navigation Using Gaussian Processes With Truncated Observations

    Page(s): 1118 - 1131
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (971 KB) |  | HTML iconHTML  

    In this paper, we consider mobile sensor networks that use spatiotemporal Gaussian processes to predict a wide range of spatiotemporal physical phenomena. Nonparametric Gaussian process regression that is based on truncated observations is proposed for mobile sensor networks with limited memory and computational power. We first provide a theoretical foundation of Gaussian process regression with truncated observations. In particular, we demonstrate that prediction using all observations can be well approximated by prediction using truncated observations under certain conditions. Inspired by the analysis, we then propose a centralized navigation strategy for mobile sensor networks to move in order to reduce prediction error variances at points of interest. For the case in which each agent has a limited communication range, we propose a distributed navigation strategy. Particularly, we demonstrate that mobile sensing agents with the distributed navigation strategy produce an emergent, swarming-like, collective behavior for communication connectivity and are coordinated to improve the quality of the collective prediction capability. View full abstract»

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  • Task-Oriented Kinematic Design of a Symmetric Assistive Climbing Robot

    Page(s): 1132 - 1137
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (362 KB) |  | HTML iconHTML  

    ASIBOT is an assistive climbing robot that is capable of aiding in daily tasks from fixed docking stations in the environment. A task-oriented design process was applied to improve the robot kinematic structure, which was based on the grid method. Twelve different robot designs were optimized for typical kitchen scenarios, followed by a quantitative comparison. View full abstract»

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  • An Analytic-Iterative Redundancy Resolution Scheme for Cable-Driven Redundant Parallel Manipulators

    Page(s): 1137 - 1143
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (520 KB) |  | HTML iconHTML  

    In this paper, redundancy resolution of a cable-driven parallel manipulator is performed through an analytic-iterative scheme. The redundancy resolution scheme is formulated as a convex optimization problem with inequality constraints that are imposed by manipulator structure and cable dynamics. The Karush-Kuhn-Tucker theorem is used to analyze the optimization problem and to draw an analytic-iterative solution for it. Subsequently, a tractable and iterative search algorithm is proposed to implement the redundancy resolution of such redundant manipulators. Furthermore, it is shown through simulations that the worst case and average elapsed time that is required to implement the proposed redundancy resolution scheme in a closed-loop implementation is considerably less than that of other numerical optimization methods. View full abstract»

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  • Online Trajectory Scaling for Manipulators Subject to High-Order Kinematic and Dynamic Constraints

    Page(s): 1144 - 1152
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (870 KB) |  | HTML iconHTML  

    Robotic manipulators are usually driven by means of minimum-time trajectories. Unfortunately, such trajectories strongly solicit the actuators whose dynamic limits could be easily exceeded. Therefore, kinematic and/or dynamic constraints are commonly considered for offline planning. Nevertheless, during actual operations, dynamic limits could be violated because of model uncertainties and measurement noise, thus causing performance losses. In order to fulfill the given bounds with certainty, planned trajectories are typically online scaled, by accounting for generalized force (GF) constraints. The resulting command signal is typically discontinuous; therefore, the system mechanics are unnecessarily solicited, and nonmodeled dynamics are excited. Moreover, in the case of systems that admit limited derivatives for GFs, tracking accuracy worsens. To prevent possible problems that derive from GF discontinuities, this paper proposes an online trajectory scaling approach that accounts for the simultaneous existence of joint constraints on GFs and their derivatives. At the same time, it is able to manage bounds on joint velocities, accelerations, and jerks. View full abstract»

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  • Sequential Composition for Navigating a Nonholonomic Cart in the Presence of Obstacles

    Page(s): 1152 - 1159
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (518 KB) |  | HTML iconHTML  

    In this study, we consider the problem of safely steering a planar nonholonomic cart around obstacles to reach a goal state. We achieve this by the decomposition of the free workspace into triangular tori and generation of local smooth feedback laws that drive the robot from one cell to an adjoining cell. These control laws exploit the fact that for nonholonomic systems, one can generate smooth controllers to reach a particular subset in the configuration space, even though smooth feedback laws cannot be obtained to reach a particular state. These local controllers are then sequenced using discrete motion planning algorithms like A* or incremental D* to reach the goal. We demonstrate the practical efficacy of this methodology by applying it to two experimental platforms: (1) a differential drive robot in which inertial effects are negligible and (2) a hexapedal robot in which inertial effects are significant but difficult to model. In both cases, we use the abstraction of a planar kinematic cart with process noise to develop feedback controllers. We present successful implementation of the controllers to navigate the hexapedal robot in both static and dynamic environments with obstacles. View full abstract»

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  • Collision Cones for Quadric Surfaces

    Page(s): 1159 - 1166
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    The problem of collision prediction in dynamic environments appears in several diverse fields, which include robotics, air vehicles, underwater vehicles, and computer animation. In this paper, collision prediction of objects that move in 3-D environments is considered. Most work on collision prediction assumes objects to be modeled as spheres. However, there are many instances of object shapes where an ellipsoidal or a hyperboloid-like bounding box would be more appropriate. In this paper, a collision cone approach is used to determine collision between objects whose shapes can be modeled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained in the form of analytical expressions in the relative velocity space. For objects of arbitrary shapes, exact representations of planar sections of the 3-D collision cone are obtained. View full abstract»

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  • Motion-Estimation-Based Visual Servoing of Nonholonomic Mobile Robots

    Page(s): 1167 - 1175
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (596 KB) |  | HTML iconHTML  

    A 2-1/2-D visual servoing strategy, which is based on a novel motion-estimation technique, is presented for the stabilization of a nonholonomic mobile robot (which is also called the “parking problem”). By taking into account the planar motion constraint of mobile robots, the proposed motion-estimation technique can be applied in both planar and nonplanar scenes. In addition, this approach requires no matrix estimation or decomposition, and it avoids ambiguity and degeneracy problems for the homography or fundamental matrix-based algorithms. Moreover, the field-of-view (FOV) constraint of the onboard camera is largely alleviated because the presented algorithm works well with few feature points. In order to incorporate the advantages of position-based visual servoing and image-based visual servoing, a composite error vector is defined that includes both image signals and the estimated rotational angle. Subsequently, a smooth time-varying feedback controller is adopted to cope with the nonholonomic constraints, which yields global exponential convergent rate for the closed-loop system. On the basis of the perturbed linear system theory, we show that practical exponential stability can be achieved, despite the lack of depth information, which is inherent for monocular camera systems. Both simulation and experiment results are collected to investigate the feasibility of the proposed approach. View full abstract»

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  • IEEE Foundation [advertisement]

    Page(s): 1176
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  • 2011 Index IEEE Transactions on Robotics Vol. 27

    Page(s): 1177 - 1190
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  • IEEE Robotics and Automation Society Information

    Page(s): C3
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  • IEEE Transactions on Robotics information for authors

    Page(s): C4
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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.

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Meet Our Editors

Editor-in-Chief
Frank Park
Seoul National University