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2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yuquan Wang Christian Smith Yiannis Karayiannidis Petter Ögren Computer Vision and Active Perception Lab. Royal Institute of Technology (KTH) Stockholm Sweden Department of Signal and Systems Chalmers University of Technology Gothenburg Sweden

In the future mobile dual-arm robots are expected to perform many tasks. Kinematically, the configuration of two manipulators that branch from the same common mobile base results in a serial-to-parallel kinematic structure, which makes inverse kinematic computations non-trivial. The motion of the base has to be decided in a trade-off, taking the needs of both arms into account. We propose to use a Virtual Kinematic Chain (VKC) to specify the common motion of the parallel manipulators, instead of using the two manipulators kinematics directly. With this VKC, we formulate a constraint based programming solution for the robot to respond to external disturbances during task execution. The proposed approach is experimentally verified both in a noise-free illustrative simulation and a real human robot co-manipulation task.

关键词： Kinematics Robot kinematics Mobile communication Manipulators Jacobian matrices Programming

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A High Level Decentralized Tracking Algorithm for Three Manipulators subject to Motion Constraints

A High Level Decentralized Tracking Algorithm for Three Mani...

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World Congress on Intelligent Control and Automation

作者： Lin Wang Johan Markdahl Xiaoming Hu Danica Kragic Department of Automation Shanghai Jiao Tong University Division of Optimization and Systems Theory Royal Institute of Technology Computer Vision and Active Perception Lab Royal Institute of Technology

ISBN: (纸本)9781467313971

This paper considers a tracking problem for three manipulators grasping a rigid object. The control objective is to coordinate the movements of the manipulators using local information in order to align the object attitude with a desired rest attitude and the object position with a time parameterized reference trajectory. The object rigidity is modelled as a constraint on the motion of the end-effectors saying that the distance between any pair of end-effectors must be constant in time. The control law consists of a rotational part and a translational part. The translational part also incorporates a linear observer of the reference trajectory. We prove stability and illustrate the system dynamics by simulation.

关键词： Decentralized control Formation control Attitude control Rigid-body motion

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What's in the Container? Classifying Object Contents from vision and Touch

What's in the Container? Classifying Object Contents from Vi...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Puren Guler Yasemin Bekiroglu Xavi Gratal Karl Pauwels Danica Kragic Computer Vision and Active Perception Lab Center for Autonomous Systems School of Computer Science and Communication KTH Royal Institute of Technology Stockholm Sweden Computer Architecture and Technology Department University of Granada Spain

ISBN: (纸本)9781479969357

Robots operating in household environments need to interact with food containers of different types. Whether a container is filled with milk, juice, yogurt or coffee may affect the way robots grasp and manipulate the container. In this paper, we concentrate on the problem of identifying what kind of content is in a container based on tactile and/or visual feedback in combination with grasping. In particular, we investigate the benefits of using unimodal (visual or tactile) or bimodal (visual-tactile) sensory data for this purpose. We direct our study toward cardboard containers with liquid or solid content or being empty. The motivation for using grasping rather than shaking is that we want to investigate the content prior to applying manipulation actions to a container. Our results show that we achieve comparable classification rates with unimodal data and that the visual and tactile data are complimentary.

关键词： CONTAINERS Grasp Robot Food Containers dry matter content NONVOLATILE CONTENT Visualization Unimodal

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Online Kinematics Estimation for active Human-Robot Manipulation of Jointly Held Objects

Online Kinematics Estimation for Active Human-Robot Manipula...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Yiannis Karayiannidis Christian Smith Francisco E. Vina 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.

ISBN: (纸本)9781467363563

This paper introduces a method for estimating the constraints imposed by a human agent on a jointly manipulated object. These estimates can be used to infer knowledge of where the human is grasping an object, enabling the robot to plan trajectories for manipulating the object while subject to the constraints. We describe the method in detail, motivate its validity theoretically, and demonstrate its use in co-manipulation tasks with a real robot.

关键词： constraints object while estimating Constraint Robot kinematics trajectory Does manipulate objects AT-Rich Interactive Domain-Containing Protein 1A

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Task-based Grasp Adaptation on a Humanoid Robot

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IFAC Proceedings Volumes 2012年第22期45卷 779-786页

作者： Jeannette Bohg Kai Welke Beatriz León Martin Do Dan Song Walter Wohlkinger Marianna Madry Aitor Aldóma Markus Przybylski Tamim Asfour Higinio Martí Danica Kragic Antonio Morales Markus Vincze Humanoids and Intelligence Systems Lab Institute for Anthropomatics KIT DE Autonomous Motion Lab MPI for Intelligent Systems DE Robotic Intelligence Laboratory Department of Computer Science and Engineering UJI ES Computer Vision and Active Perception lab KTH SE Automation and Control Institute TUW AT

In this paper, we present an approach towards autonomous grasping of objects according to their category and a given task. Recent advances in the field of object segmentation and categorization as well as task-based grasp inference have been leveraged by integrating them into one pipeline. This allows us to transfer task-specific grasp experience between objects of the same category. The effectiveness of the approach is demonstrated on the humanoid robot ARMAR-IIIa.

关键词： Robotic Grasping and Manipulation Task-based Grasp Synthesis Visual Servoing Attention Segmentation Object categorization System Integration

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Bimanual folding assembly: Switched control and contact point estimation

Bimanual folding assembly: Switched control and contact poin...

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IEEE-RAS International Conference on Humanoid Robots

作者： Diogo Almeida Francisco E. Viña Yiannis Karayiannidis Computer Vision and Active Perception Lab. Royal Institute of Technology KTH Stockholm Sweden Dept. of Signals and Systems Chalmers University of Technology Gothenburg Sweden

ISBN: (纸本)9781509047192

Robotic assembly in unstructured environments is a challenging task, due to the added uncertainties. These can be mitigated through the employment of assembly systems, which offer a modular approach to the assembly problem via the conjunction of primitives. In this paper, we use a dual-arm manipulator in order to execute a folding assembly primitive. When executing a folding primitive, two parts are brought into rigid contact and posteriorly translated and rotated. A switched controller is employed in order to ensure that the relative motion of the parts follows the desired model, while regulating the contact forces. The control is complemented with an estimator based on a Kalman filter, which tracks the contact point between parts based on force and torque measurements. Experimental results are provided, and the effectiveness of the control and contact point estimation is shown.

关键词： Robot kinematics Estimation Force Robot sensing systems Switches

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A Hybrid Control Approach to Task Priority Based Mobile Manipulation

A Hybrid Control Approach to Task Priority Based Mobile Mani...

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IEEE Annual Conference on Decision and Control

作者： J. Markdahl X. Hu D. Kragic Y. Karayiannidis Division of Optimization and Systems Theory KTH Royal Institute of Technology Stockholm Sweden Computer Vision and Active Perception Lab KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781479978878

This paper proposes a hybrid control approach to task priority based mobile manipulation. More specifically, it uses a hybrid systems framework to address the problem of end-effector path following for a manipulator attached to a nonholonomic mobile platform where the joints are subject to constraints and the inputs signals are required to be bounded. A switched control strategy allows the robot to avoid infeasible and singular joint configurations while executing a bounded pseudo-inverse based feedback control law. The resulting closed loop system stabilizes the desired path, has a dwell time in each mode, and only switches a finite number of times.

关键词： Mobile communication Manipulators Kinematics Switches Vehicles

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Caging Complex Objects with Geodesic Balls

Caging Complex Objects with Geodesic Balls

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Dmitry Zarubin Florian T. Pokorny Marc Toussaint Danica Kragic Machine Learning and Robotics Lab Universitat Stuttgart Stuttgart Germany Centre for Autonomous Systems Computer Vision and Active Perception Lab School of Computer Science and Communication KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467363563

This paper proposes a novel approach for the synthesis of grasps of objects whose geometry can be observed only in the presence of noise. We focus in particular on the problem of generating caging grasps with a realistic robot hand simulation and show that our method can generate such grasps even on complex objects. We introduce the idea of using geodesic balls on the object's surface in order to approximate the maximal contact surface between a robotic hand and an object. We define two types of heuristics which extract information from approximate geodesic balls in order to identify areas on an object that can likely be used to generate a caging grasp. Our heuristics are based on two scoring functions. The first uses winding angles measuring how much a geodesic ball on the surface winds around a dominant axis, while the second explores using the total discrete Gaussian curvature of a geodesic ball to rank potential caging postures. We evaluate our approach with respect to variations in hand kinematics, for a selection of complex real-world objects and with respect to its robustness to noise.

关键词： Caging Complex Objects Geodesic Balls Gaussian curvature

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Filling the gap between low frequency measurements with their estimates

Filling the gap between low frequency measurements with thei...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yuquan Wang Dragan Kostić Sven T. H. Jansen Henk Nijmeijer Computer Vision and Active Perception Lab Royal Institute of Technology Stockholm The Mechanical Engineering department Eindhoven University of Technology Eindhoven Technical Sciences/Automotive department TNO Helmond

The use of redundant sensors brings a rich diversity of information, nevertheless fusing different sensors that run at vastly different frequencies into a proper estimate is still a challenging sensor fusion problem. Instead of using the size-varying measurements and thereby the size-varying filters during each sampling period, we propose to find a substitute of the unavailable low frequency measurements such that we can avoid using different sampling frequencies in one filter. In the gap between the sampling of two low frequency measurements, the use of these substitutes produces smoother estimates. In both the proof of concept simulation and the localization experiment performed on an indoor soccer robot, our proposed approach exhibits an improved performance compared to the size-varying Kalman filter methods.

关键词： Frequency measurement Kalman filters Time measurement Sensor fusion Switches Robots Vectors

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Generalizing grasps across partly similar objects

Generalizing grasps across partly similar objects

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Renaud Detry Carl Henrik Ek Marianna Madry Justus Piater Danica Kragic Centre for Autonomous Systems and the Computer Vision and Active Perception Lab CSC KTH Royal Institute of Technology Stockholm Sweden Intelligent and Interactive Systems group Institute of Computer Science University of Innsbruck Austria

The paper starts by reviewing the challenges associated to grasp planning, and previous work on robot grasping. Our review emphasizes the importance of agents that generalize grasping strategies across objects, and that are able to transfer these strategies to novel objects. In the rest of the paper, we then devise a novel approach to the grasp transfer problem, where generalization is achieved by learning, from a set of grasp examples, a dictionary of object parts by which objects are often grasped. We detail the application of dimensionality reduction and unsupervised clustering algorithms to the end of identifying the size and shape of parts that often predict the application of a grasp. The learned dictionary allows our agent to grasp novel objects which share a part with previously seen objects, by matching the learned parts to the current view of the new object, and selecting the grasp associated to the best-fitting part. We present and discuss a proof-of-concept experiment in which a dictionary is learned from a set of synthetic grasp examples. While prior work in this area focused primarily on shape analysis (parts identified, e.g., through visual clustering, or salient structure analysis), the key aspect of this work is the emergence of parts from both object shape and grasp examples. As a result, parts intrinsically encode the intention of executing a grasp.

关键词： Grasping Shape Planning Dictionaries Databases Grippers Covariance matrix

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