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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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Predicting slippage and learning manipulation affordances through Gaussian Process regression

Predicting slippage and learning manipulation affordances th...

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IEEE-RAS International Conference on Humanoid Robots

作者： Francisco E. Viña B. Yasemin Bekiroglu 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 Computer Vision and Active Perception Lab Royal Institute of Technology KTH Stockholm Sweden

Object grasping is commonly followed by some form of object manipulation - either when using the grasped object as a tool or actively changing its position in the hand through in-hand manipulation to afford further interaction. In this process, slippage may occur due to inappropriate contact forces, various types of noise and/or due to the unexpected interaction or collision with the environment. In this paper, we study the problem of identifying continuous bounds on the forces and torques that can be applied on a grasped object before slippage occurs. We model the problem as kinesthetic rather than cutaneous learning given that the measurements originate from a wrist mounted force-torque sensor. Given the continuous output, this regression problem is solved using a Gaussian Process approach. We demonstrate a dual armed humanoid robot that can autonomously learn force and torque bounds and use these to execute actions on objects such as sliding and pushing. We show that the model can be used not only for the detection of maximum allowable forces and torques but also for potentially identifying what types of tasks, denoted as manipulation affordances, a specific grasp configuration allows. The latter can then be used to either avoid specific motions or as a simple step of achieving in-hand manipulation of objects through interaction with the environment.

关键词： Friction Robot sensing systems Force Torque Grasping

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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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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

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.

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

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Task-based grasp adaptation on a humanoid robot

Task-based grasp adaptation on a humanoid robot

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10th IFAC Symposium on Robot Control, SYROCO 2012

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

ISBN: (纸本)9783902823113

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. © 2012 IFAC.

关键词： Anthropomorphic robots

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In-hand manipulation using gravity and controlled slip

In-hand manipulation using gravity and controlled slip

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

作者： Vina B., Francisco E. Karayiannidis, Yiannis Pauwels, Karl 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)9781479999941

In this work we propose a sliding mode controller for in-hand manipulation that repositions a tool in the robot's hand by using gravity and controlling the slippage of the tool. In our approach, the robot holds the tool with a pinch grasp and we model the system as a link attached to the gripper via a passive revolute joint with friction, i.e., the grasp only affords rotational motions of the tool around a given axis of rotation. The robot controls the slippage by varying the opening between the fingers in order to allow the tool to move to the desired angular position following a reference trajectory. We show experimentally how the proposed controller achieves convergence to the desired tool orientation under variations of the tool's inertial parameters. © 2015 IEEE.

关键词： Sliding mode control

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Classical Grasp Quality Evaluation: New Algorithms and Theory

Classical Grasp Quality Evaluation: New Algorithms and Theor...

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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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Estimating the Deformability of Elastic Materials using Optical Flow and Position-based Dynamics

Estimating the Deformability of Elastic Materials using Opti...

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IEEE-RAS International Conference on Humanoid Robots

作者： Puren Guler Karl Pauwels Alessandro Pieropan Hedvig Kjellstrom Danica Kragic Computer Vision and Active Perception Lab Center for Autonomous Systems School of Computer Science and Communication KTH Royal Institute of Technology

ISBN: (纸本)9781479968862

Knowledge of the physical properties of objects is essential in a wide range of robotic manipulation scenarios. A robot may not always be aware of such properties prior to interaction. If an object is incorrectly assumed to be rigid, it may exhibit unpredictable behavior when grasped. In this paper, we use vision based observation of the behavior of an object a robot is interacting with and use it as the basis for estimation of its elastic deformability. This is estimated in a local region around the interaction point using a physics simulator. We use optical flow to estimate the parameters of a position-based dynamics simulation using meshless shape matching (MSM). MSM has been widely used in computer graphics due to its computational efficiency, which is also important for closed-loop control in robotics. In a controlled experiment we demonstrate that our method can qualitatively estimate the physical properties of objects with different degrees of deformability.

关键词： Deformability Optic Flow Unpredictable behavior physical properties elastic materials Behavior Observation Techniques Robot kinetic simulation computer GRAPHICS MSM Computational efficiency robotics

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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

关键词： Friction

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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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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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