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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Florian T. Pokorny Danica Kragic Computer Vision and Active Perception Lab Centre for Autonomous Systems KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467363563

This paper investigates theoretical properties of a well-known L~1 grasp quality measure Q whose approximation Q_l~- is commonly used for the evaluation of grasps and where the precision of Q_l~- depends on an approximation of a cone by a convex polyhedral cone with l edges. We prove the Lipschitz continuity of Q and provide an explicit Lipschitz bound that can be used to infer the stability of grasps lying in a neighbourhood of a known grasp. We think of Q_l~- as a lower bound estimate to Q and describe an algorithm for computing an upper bound Q~+. We provide worst-case error bounds relating Q and Q_l~-. Furthermore, we develop a novel grasp hypothesis rejection algorithm which can exclude unstable grasps much faster than current implementations. Our algorithm is based on a formulation of the grasp quality evaluation problem as an optimization problem, and we show how our algorithm can be used to improve the efficiency of sampling based grasp hypotheses generation methods.

关键词： New Algorithms Theory evaluation of grasps Grasp theories Quality factor formula quality evaluation approximate formula algorithms Lower bound Neighborhood

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Task modeling in imitation learning using latent variable models

Task modeling in imitation learning using latent variable mo...

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IEEE-RAS International Conference on Humanoid Robots

作者： Carl Henrik Ek Dan Song Kai Huebner Danica Kragic Computer Vision & Active Perception Laboratory Center of Autonomous Systems KTH Royal Institute of Technology Stockholm Sweden

An important challenge in robotic research is learning and reasoning about different manipulation tasks from scene observations. In this paper we present a probabilistic model capable of modeling several different types of input sources within the same model. Our model is capable to infer the task using only partial observations. Further, our framework allows the robot, given partial knowledge of the scene, to reason about what information streams to acquire in order to disambiguate the state-space the most. We present results for task classification within and also reason about different features discriminative power for different classes of tasks.

关键词： Data models Robot sensing systems Humans Training Feature extraction Training data

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Adaptive Force/Velocity control for opening unknown doors 1

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IFAC Proceedings Volumes 2012年第22期45卷 753-758页

作者： Yiannis Karayiannidis Christian Smith Petter Ögren Danica Kragic Computer Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication Royal Institute of Technology (KTH) SE-100 44 Stockholm Sweden

The problem of door opening is fundamental for robots operating in domestic environments. Since these environments are generally unstructured, a robot must deal with several types of uncertainties associated with the dynamics and kinematics of a door to achieve successful opening. The present paper proposes a dynamic force/velocity controller which uses adaptive estimation of the radial direction based on adaptive estimates of the door hinge's position. The control action is decomposed into estimated radial and tangential directions, which are proved to converge to the corresponding actual values. The force controller uses reactive compensation of the tangential forces and regulates the radial force to a desired small value, while the velocity controller ensures that the robot's end-effector moves with a desired tangential velocity. The performance of the control scheme is demonstrated in simulation with a 2 DoF planar manipulator opening a door.

关键词： door opening force/velocity control adaptive estimation

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Object recognition using saliency maps and HTM learning

Object recognition using saliency maps and HTM learning

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2012 IEEE International Conference on Imaging systems and Techniques, IST 2012

作者： Kostavelis, Ioannis Nalpantidis, Lazaros Gasteratos, Antonios Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Vas. Sofias 12 GR-67100 Xanthi Greece Computer Vision and Active Perception Lab. Centre for Autonomous Systems Royal Institute of Technology - KTH SE-100 44 Stockholm Sweden

ISBN: (纸本)9781457717741

In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations. In accordance with HTM's biological inspiration, human vision mechanisms can be used to preprocess the input images. Therefore, the input images undergo a saliency computation step, revealing the plausible information of the scene, where a human might fixate. The adoption of the saliency detection module releases the HTM network from memorizing redundant information and augments the classification accuracy. The efficiency of the proposed framework has been experimentally evaluated in the ETH-80 dataset, and the classification accuracy has been found to be greater than other HTM systems. © 2012 IEEE.

关键词： Object recognition

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Friction Coefficients and Grasp Synthesis

Friction Coefficients and Grasp Synthesis

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Kaiyu Hang Florian T. Pokorny Danica Kragic Computer Vision and Active Perception Lab Centre for Autonomous Systems CSC KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467363563

We propose a new concept called friction sensitivity which measures how susceptible a specific grasp is to changes in the underlying friction coefficients. We develop algorithms for the synthesis of stable grasps with low friction sensitivity and for the synthesis of stable grasps in the case of small friction coefficients. We describe how grasps with low friction sensitivity can be used when a robot has an uncertain belief about friction coefficients and study the statistics of grasp quality under changes in those coefficients. We also provide a parametric estimate for the distribution of grasp qualities and friction sensitivities for a uniformly sampled set of grasps.

关键词： Friction Coefficients Grasp Synthesis underlying friction coefficients Grasp coefficient of friction friction synthesis

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A Multi Objective Control approach to Online Dual Arm Manipulation 1

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IFAC Proceedings Volumes 2012年第22期45卷 747-752页

作者： Petter Ögren Christian Smith Yiannis Karayiannidis Danica Kragic Computer Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication Royal Institute of Technology (KTH) SE-100 44 Stockholm Sweden

In this paper, we propose a new way to exploit the redundancy of dual arm mobile manipulators when performing inherently bi-manual tasks using online controllers. Bi-manual tasks are tasks that require motion of both arms in order to be carried out efficiently, such as holding and cleaning an object, or moving an object from one hand to the other. These tasks are often associated with several constraints, such as singularity- and collision avoidance, but also a high degree of redundancy, as the relative positions of the two grippers is far more important than the absolute positions, when for example handing an object from one arm to the other. By applying a modular multi objective control framework, inspired by earlier work on sub-task control, we exploit this redundancy to form a subset of the joint space that is feasible, i.e. not violating any of the constraints. Earlier approacher added the additional tasks in terms of equality constraints, thereby reducing the dimension of the feasible subset until it was a single point. Here however, we add the additional tasks in terms of inequalities, removing parts of the feasible set rather than collapsing its dimensionality. Thus, we are able to handle an arbitrary number of constraints, instead of a number corresponding to the dimension of the feasible set (degree of redundancy). Finally, inside the feasible set we choose controls stay in the set, while simultaneously minimizing some given objective. The proposed approach is illustrated by several simulation examples.

关键词： Robotic manipulators Redundant Manipulators Robot control Robot kinematics autonomous mobile robots

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Integrating object and grasp recognition for dynamic scene interpretation

Integrating object and grasp recognition for dynamic scene i...

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International Conference on Advanced Robotics (ICAR)

作者： S. Ekvall D. Kragic Computational Vision and Active Perception Laboratory Centre for Autonomous Systems Department of Numerical Analysis and Computer Science Royal Institute of Technology Stockholm Sweden

Understanding and interpreting dynamic scenes and activities is a very challenging problem. In this paper, we present a system capable of learning robot tasks from demonstration. Classical robot task programming requires an experienced programmer and a lot of tedious work. In contrast, programming by demonstration is a flexible framework that reduces the complexity of programming robot tasks, and allows end-users to demonstrate the tasks instead of writing code. We present our recent steps towards this goal. A system for learning pick-and-place tasks by manually demonstrating them is presented. Each demonstrated task is described by an abstract model involving a set of simple tasks such as what object is moved, where it is moved, and which grasp type was used to move it

关键词： Layout Robot programming Writing Humans Sensor phenomena and characterization Object recognition computer vision Laboratories Numerical analysis computer science

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Monocular real-time 3D articulated hand pose estimation

Monocular real-time 3D articulated hand pose estimation

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IEEE-RAS International Conference on Humanoid Robots

作者： Javier Romero Hedvig Kjellström Danica Kragic Computational Vision and Active Perception Laboratory Centre for Autonomous Systems School of Computer Science and Communication KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781424445875

Markerless, vision based estimation of human hand pose over time is a prerequisite for a number of robotics applications, such as learning by demonstration (LbD), health monitoring, teleoperation, human-robot interaction. It has special interest in humanoid platforms, where the number of degrees of freedom makes conventional programming challenging. Our primary application is LbD in natural environments where the humanoid robot learns how to grasp and manipulate objects by observing a human performing a task. This paper presents a method for continuous vision based estimation of human hand pose. The method is non-parametric, performing a nearest neighbor search in a large database (100000 entries) of hand pose examples. The main contribution is a real time system, robust to partial occlusions and segmentation errors, that provides full hand pose recognition from markerless data. An additional contribution is the modeling of constraints based on temporal consistency in hand pose, without explicitly tracking the hand in the high dimensional pose space. The pose representation is rich enough to enable a descriptive human-to-robot mapping. Experiments show the pose estimation to be more robust and accurate than a non-parametric method without temporal constraints.

关键词： Humanoid robots Real time systems Robustness Human robot interaction Robot vision systems Fingers computer vision computer science Application software computerized monitoring

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Interactive object classification using sensorimotor contingencies

Interactive object classification using sensorimotor conting...

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Virgile Hogman Marten Bjorkman Danica Kragic Centre for Autonomous Systems Computer Vision and Active Perception Lab CSC KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467363563

Understanding and representing objects and their function is a challenging task. Objects we manipulate in our daily activities can be described and categorized in various ways according to their properties or affordances, depending also on our perception of those. In this work, we are interested in representing the knowledge acquired through interaction with objects, describing these in terms of action-effect relations, i.e. sensorimotor contingencies, rather than static shape or appearance representations. We demonstrate how a robot learns sensorimotor contingencies through pushing using a probabilistic model. We show how functional categories can be discovered and how entropy-based action selection can improve object classification.

关键词： Robot sensing systems Shape Data models Predictive models Gaussian processes Uncertainty

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Integrated Motion and Clasp Planning with Virtual Linking

Integrated Motion and Clasp Planning with Virtual Linking

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Johannes A. Stork Florian T. Pokorny Danica Kragic Computer Vision and Active Perception Lab Centre for Autonomous Systems CSC KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467363563

In this work, we address the problem of simultaneous clasp and motion planning on unknown objects with holes. Clasping an object enables a rich set of activities such as dragging, toting, pulling and hauling which can be applied to both soft and rigid objects. To this end, we define a virtual linking measure which characterizes the spacial relation between the robot hand and object. The measure utilizes a set of closed curves arising from an approximately shortest basis of the object's first homology group. We define task spaces to perform collision-free motion planing with respect to multiple prioritized objectives using a sampling-based planing method. The approach is tested in simulation using different robot hands and various real-world objects.

关键词： Integrated Motion Clasp Planning Virtual Linking robotic hand Hooks Yard motion planning Planing Virtual Holes Closed curve

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