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共 71 条记录，以下是21-30 订阅

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Learning Predictive State Representations for planning

Learning Predictive State Representations for planning

引用

IEEE/RSJ International Conference on Intelligent Robots and systems

作者： J. A. Stork C. H. Ek D. Kragic Computer Vision and Active Perception Lab Centre for Autonomous Systems KTH Royal Institute of Technology Stockholm Sweden Computer Vision and Active Perception Lab Centre for Autonomous Systems School of Computer Science and Communication KTH Royal Institute of Technology Stockholm Sweden

Predictive State Representations (PSRs) allow modeling of dynamical systems directly in observables and without relying on latent variable representations. A problem that arises from learning PSRs is that it is often hard to attribute semantic meaning to the learned representation. This makes generalization and planning in PSRs challenging. In this paper, we extend PSRs and introduce the notion of PSRs that include prior information (P-PSRs) to learn representations which are suitable for planning and interpretation. By learning a low-dimensional embedding of test features we map belief points of similar semantic to the same region of a subspace. This facilitates better generalization for planning and semantical interpretation of the learned representation. In specific, we show how to overcome the training sample bias and introduce feature selection such that the resulting representation emphasizes observables related to the planning task. We show that our P-PSRs result in qualitatively meaningful representations and present quantitative results that indicate improved suitability for planning.

关键词： Planning History Robots Semantics Predictive models Uncertainty

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Adaptive control for pivoting with visual and tactile feedback

Adaptive control for pivoting with visual and tactile feedba...

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2016 IEEE International Conference on Robotics and Automation, ICRA 2016

作者： Vina, Francisco E.B. Karayiannidis, Yiannis Smith, Christian Kragic, Danica Computer Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication Royal Institute of Technology KTH StockholmSE-100 44 Sweden Dept. of Signals and Systems Chalmers University of Technology GothenburgSE-412 96 Sweden

ISBN: (纸本)9781467380263

In this work we present an adaptive control approach for pivoting, which is an in-hand manipulation maneuver that consists of rotating a grasped object to a desired orientation relative to the robot's hand. We perform pivoting by means of gravity, allowing the object to rotate between the fingers of a one degree of freedom gripper and controlling the gripping force to ensure that the object follows a reference trajectory and arrives at the desired angular position. We use a visual pose estimation system to track the pose of the object and force measurements from tactile sensors to control the gripping force. The adaptive controller employs an update law that accommodates for errors in the friction coefficient, which is one of the most common sources of uncertainty in manipulation. Our experiments confirm that the proposed adaptive controller successfully pivots a grasped object in the presence of uncertainty in the object's friction parameters. © 2016 IEEE.

关键词： Friction

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Grasping objects with holes: A topological approach

Grasping objects with holes: A topological approach

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Florian T. Pokorny Johannes A. Stork Danica Kragic Computer Vision and Active Perception Laboratory Centre for Autonomous Systems School of Computer Science and Communication Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467356404

This work proposes a topologically inspired approach for generating robot grasps on objects with `holes'. Starting from a noisy point-cloud, we generate a simplicial representation of an object of interest and use a recently developed method for approximating shortest homology generators to identify graspable loops. To control the movement of the robot hand, a topologically motivated coordinate system is used in order to wrap the hand around such loops. Finally, another concept from topology - namely the Gauss linking integral - is adapted to serve as evidence for secure caging grasps after a grasp has been executed. We evaluate our approach in simulation on a Barrett hand using several target objects of different sizes and shapes and present an initial experiment with real sensor data.

关键词： Noise measurement Robots Jacobian matrices

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Integrating active Mobile Robot Object Recognition and SLAM in Natural Environments

Integrating Active Mobile Robot Object Recognition and SLAM ...

引用

2006 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Staffan Ekvall Patric Jensfelt Danica Kragic Computational Vision and Active Perception Laboratory and Centre for Autonomous Systems Royal Institute of Technology Stockholm Sweden

Linking semantic and spatial information has become an important research area in robotics since, for robots interacting with humans and performing tasks in natural environments, it is of foremost importance to be able to reason beyond simple geometrical and spatial levels. In this paper, we consider this problem in a service robot scenario where a mobile robot autonomously navigates in a domestic environment, builds a map as it moves along, localizes its position in it, recognizes objects on its way and puts them in the map. The experimental evaluation is performed in a realistic setting where the main concentration is put on the synergy of object recognition and simultaneous localization and mapping systems

关键词： Mobile robots Object recognition Simultaneous localization and mapping Robot kinematics Human robot interaction Robot vision systems Robot sensing systems Intelligent robots Navigation Robotics and automation

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Adaptive Virtual Fixtures for Machine-Assisted Teleoperation Tasks

Adaptive Virtual Fixtures for Machine-Assisted Teleoperation...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： D. Aarno S. Ekvall D. Kragic Centre for Autonomous Systems Computational Vision and Active Perception Laboratory Royal Institute of Technology Stockholm Sweden

It has been demonstrated in a number of robotic areas how the use of virtual fixtures improves task performance both in terms of execution time and overall precision, [1]. However, the fixtures are typically inflexible, resulting in a degraded performance in cases of unexpected obstacles or incorrect fixture models. In this paper, we propose the use of adaptive virtual fixtures that enable us to cope with the above problems. A teleoperative or human machine collaborative setting is assumed with the core idea of dividing the task, that the operator is executing, into several subtasks. The operator may remain in each of these subtasks as long as necessary and switch freely between them. Hence, rather than executing a predefined plan, the operator has the ability to avoid unforeseen obstacles and deviate from the model. In our system, the probability that the user is following a certain trajectory (subtask) is estimated and used to automatically adjusts the compliance. Thus, an on-line decision of how to fixture the movement is provided.

关键词： Fixtures Humans Hidden Markov models Man machine systems Surgery Robotic assembly Collaboration Switches Collaborative work Assembly systems

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Layered HMM for Motion Intention Recognition

Layered HMM for Motion Intention Recognition

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2006 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Daniel Aarno Danica Kragic School of Computer Science and Communication Centre for Autonomous Systems-Computational Vision and Active Perception Laboratory Royal Institute of Technology Sweden

Acquiring, representing and modeling human skills is one of the key research areas in teleoperation, programming-by-demonstration and human-machine collaborative settings. One of the common approaches is to divide the task that the operator is executing into several subtask in order to provide manageable modeling. In this paper we consider the use of a layered hidden Markov model (LHMM) to model human skills. We evaluate a gestem classifier that classifies motions into basic action-primitives, or gestems. The gestem classifiers are then used in a LHMM to model a simulated teleoperated task. We investigate the online and offline classification performance with respect to noise, number of gestems, type of HMM and the available number of training sequences. We also apply the LHMM to data recorded during the execution of a trajectory-tracking task in 2D and 3D with a robotic manipulator in order to give qualitative as well as quantitative results for the proposed approach. The results indicate that the LHMM is suitable for modeling teleoperative trajectory-tracking tasks and that the difference in classification performance between one and multi-dimensional HMMs for gestem classification are small. It can also be seen that the LHMM is robust w.r.t misclassifications in the underlying gestem classifiers

关键词： Hidden Markov models Intelligent robots Man machine systems Collaboration Learning Human robot interaction Robotics and automation Speech recognition Character recognition computer vision

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Learning and Evaluation of the Approach Vector for Automatic Grasp Generation and Planning

Learning and Evaluation of the Approach Vector for Automatic...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Staffan Ekvall Danica Kragic Computational Vision and Active Perception Laboratory Centre for Autonomous Systems Royal Institute of Technology Stockholm Sweden

In this paper, we address the problem of automatic grasp generation for robotic hands where experience and shape primitives are used in synergy so to provide a basis not only for grasp generation but also for a grasp evaluation process when the exact pose of the object is not available. One of the main challenges in automatic grasping is the choice of the object approach vector, which is dependent both on the object shape and pose as well as the grasp type. Using the proposed method, the approach vector is chosen not only based on the sensory input but also on experience that some approach vectors will provide useful tactile information that finally results in stable grasps. A methodology for developing and evaluating grasp controllers is presented where the focus lies on obtaining stable grasps under imperfect vision. The method is used in a teleoperation or a programming by demonstration setting where a human demonstrates to a robot how to grasp an object. The system first recognizes the object and grasp type which can then be used by the robot to perform the same action using a mapped version of the human grasping posture.

关键词： Humans Shape Robotics and automation Grasping Kinematics Robot programming Feedback Process planning Technology planning computer vision

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Integrating Grasp Planning with Online Stability Assessment using Tactile Sensing

Integrating Grasp Planning with Online Stability Assessment ...

引用

2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

作者： Yasemin Bekiroglu Kai Huebner Danica Kragic Computer Vision and Active Perception Lab Centre for Autonomous SystemsSchool of Computer Science and CommunicationKTHStockholmSweden

This paper presents an integration of grasp planning and online grasp stability assessment based on tactile data. We show how the uncertainty in grasp execution posterior to grasp planning can be dealt with using tactile sensing and machine learning techniques. The majority of the state-of-theart grasp planners demonstrate impressive results in simulation. However, these results are mostly based on perfect scene/object knowledge allowing for analytical measures to be employed. It is questionable how well these measures can be used in realistic scenarios where the information about the object and robot hand may be incomplete and/or uncertain. Thus, tactile and force-torque sensory information is necessary for successful online grasp stability assessment. We show how a grasp planner can be integrated with a probabilistic technique for grasp stability assessment in order to improve the hypotheses about suitable grasps on different types of objects. Experimental evaluation with a three-fingered robot hand equipped with tactile array sensors shows the feasibility and strength of the integrated approach.

关键词： Hidden Markov models Stability analysis Tactile sensors Grasping

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YES - YEt another object segmentation: Exploiting camera movement

YES - YEt another object segmentation: Exploiting camera mov...

引用

2012 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Lazaros Nalpantidis Mårten Björkman Danica Kragic Computer Vision and Active Perception Laboratory Centre for Autonomous Systems School of Computer Science and Communication Royal Institute of Technology (KTH) Stockholm Sweden

We address the problem of object segmentation in image sequences where no a-priori knowledge of objects is assumed. We take advantage of robots' ability to move, gathering multiple images of the scene. Our approach starts by extracting edges, uses a polar domain representation and performs integration over time based on a simple dilation operation. The proposed system can be used for providing reliable initial segmentation of unknown objects in scenes of varying complexity, allowing for recognition, categorization or physical interaction with the objects. The experimental evaluation on both self-captured and a publicly available dataset shows the efficiency and stability of the proposed method.

关键词： Image edge detection Image segmentation Object segmentation Correlation Optical imaging Robots Detectors

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Adaptive control for pivoting with visual and tactile feedback

Adaptive control for pivoting with visual and tactile feedba...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Francisco E. Viña B. Yiannis Karayiannidis Christian Smith Danica Kragic Computer Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication Royal Institute of Technology KTH Stockholm Sweden Computer Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication Chalmers University of Technology Sweden Computer Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication Royal Institute of Technology KTH Sweden

关键词： Friction Force Grippers Robot kinematics Planning Robot sensing systems

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