This paper presents an approach to text recognition in natural scene images. The main contribution of this paper is the efficient exploitation of colour information for the identification of text regions in the presen...
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Behavior Trees (BTs) have become a popular framework for designing controllers of in-game opponents in the computer gaming industry. In this paper, we formalize and analyze the reasons behind the success of the BTs us...
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Superpixel generation is widely used in image segmentation. In this paper, we present an efficient flooding based superpixel generation algorithm. A new distance metric is defined for estimating pixels and seeds' ...
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Through semantically grouping pixels in local neighborhoods, superpixels can capture image redundancy and significantly improve the performance of post-processing algorithms. In this paper, we investigate the applicat...
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Socially engaged methods are increasingly being used within HCI research, yet arts practice in this context has been little explored. HCI research that aligns with socially engaged arts practices encourages debate aro...
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ISBN:
(纸本)9781450324748
Socially engaged methods are increasingly being used within HCI research, yet arts practice in this context has been little explored. HCI research that aligns with socially engaged arts practices encourages debate around societal challenges;for example discussion of issues surrounding the role of digital technology in sustainability, inclusion, community, identity and the politics of participation. Building on existing research, this workshop will bring together a diverse group of HCI researchers, artists and other creators whose work or interests align with socially engaged arts practice, to foster critical exploration and creative collab.ration.
Depth sensors such as Kinect fail to find the depth of transparent objects which makes 3D reconstruction of such objects a challenge. The refinement algorithms for Kinect depth maps either do not address transparency ...
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ISBN:
(纸本)9781479952106
Depth sensors such as Kinect fail to find the depth of transparent objects which makes 3D reconstruction of such objects a challenge. The refinement algorithms for Kinect depth maps either do not address transparency or they only provide sparse depth on such objects which is inadequate for dense 3D reconstruction. In order to solve this problem, we propose a fully-connected CRF based hybrid refinement algorithm. We incorporate stereo cues from cross-modal stereo between IR and RGB cameras of the Kinect and Kinect's depth map. Our algorithm does not require any additional cameras and still provides dense depth estimations of transparent objects and specular surfaces with high accuracy.
This paper presents a unified framework for Behavior Trees (BTs), a plan representation and execution tool. The availab.e literature lacks the consistency and mathematical rigor required for robotic and control applic...
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This paper presents a unified framework for Behavior Trees (BTs), a plan representation and execution tool. The availab.e literature lacks the consistency and mathematical rigor required for robotic and control applications. Therefore, we approach this problem in two steps: first, reviewing the most popular BT literature exposing the aforementioned issues; second, describing our unified BT framework along with equivalence notions between BTs and Controlled Hybrid Dynamical Systems (CHDSs). This paper improves on the existing state of the art as it describes BTs in a more accurate and compact way, while providing insight about their actual representation capabilities. Lastly, we demonstrate the applicability of our framework to real systems scheduling open-loop actions in a grasping mission that involves a NAO robot and our BT library.
Behavior Trees (BTs) have become a popular framework for designing controllers of in-game opponents in the computer gaming industry. In this paper, we formalize and analyze the reasons behind the success of the BTs us...
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Behavior Trees (BTs) have become a popular framework for designing controllers of in-game opponents in the computer gaming industry. In this paper, we formalize and analyze the reasons behind the success of the BTs using standard tools of robot control theory, focusing on how properties such as robustness and safety are addressed in a modular way. In particular, we show how these key properties can be traced back to the ideas of subsumption and sequential compositions of robot behaviors. Thus BTs can be seen as a recent addition to a long research effort towards increasing modularity, robustness and safety of robot control software. To illustrate the use of BTs, we provide a set of solutions to example problems.
In this paper we consider the problem of human-robot collab.rative manipulation of an object, where the human is active in controlling the motion, and the robot is passively following the human's lead. Assuming th...
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In this paper we consider the problem of human-robot collab.rative manipulation of an object, where the human is active in controlling the motion, and the robot is passively following the human's lead. Assuming that the human grasp of the object only allows for transfer of forces and not torques, there is a disambiguity as to whether the human desires translation or rotation. In this paper, we analyze different approaches to this problem both theoretically and in experiment. This leads to the proposal of a control methodology that uses switching between two different admittance control modes based on the magnitude of measured force to achieve disambiguation of the rotation/translation problem.
One of the big challenges for robots working outside of traditional industrial settings is the ability to robustly and flexibly grasp and manipulate tools for various tasks. When a tool is interacting with another obj...
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One of the big challenges for robots working outside of traditional industrial settings is the ability to robustly and flexibly grasp and manipulate tools for various tasks. When a tool is interacting with another object during task execution, several problems arise: a tool can be partially or completely occluded from the robot's view, it can slip or shift in the robot's hand - thus, the robot may lose the information about the exact position of the tool in the hand. Thus, there is a need for online calibration and/or recalibration of the tool. In this paper, we present a model-free online tool-tip calibration method that uses force/torque measurements and an adaptive estimation scheme to estimate the point of contact between a tool and the environment. An adaptive force control component guarantees that interaction forces are limited even before the contact point estimate has converged. We also show how to simultaneously estimate the location and normal direction of the surface being touched by the tool-tip as the contact point is estimated. The stability of the the overall scheme and the convergence of the estimated parameters are theoretically proven and the performance is evaluated in experiments on a real robot.
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