| 1. |
- Bohg, Jeannette, et al.
(författare)
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Strategies for Multi-Modal Scene Exploration
- 2010
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Ingår i: IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010). - 9781424466757 ; , s. 4509-4515
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Konferensbidrag (refereegranskat)abstract
- We propose a method for multi-modal scene exploration where initial object hypothesis formed by active visual segmentation are confirmed and augmented through haptic exploration with a robotic arm. We update the current belief about the state of the map with the detection results and predict yet unknown parts of the map with a Gaussian Process. We show that through the integration of different sensor modalities, we achieve a more complete scene model. We also show that the prediction of the scene structure leads to a valid scene representation even if the map is not fully traversed. Furthermore, we propose different exploration strategies and evaluate them both in simulation and on our robotic platform.
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| 2. |
- Bätz, Georg, et al.
(författare)
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Ball dribbling with an underactuated continuous-time control phase : Theory & experiments
- 2010
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Ingår i: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems. - : IEEE. - 9781424466757 - 9781424466764 - 9781424466740 ; , s. 2890-2895
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Konferensbidrag (refereegranskat)abstract
- Ball dribbling is a central element of basketball. One main challenge for realizing basketball robots is to stabilize periodic motion of the ball. The task is nontrivial due to the discrete-continuous nature of the corresponding dynamics. This paper proposes to add an elastic element to the manipulator so the ball can be controlled in a continuous-time phase instead of an intermittent contact. Optimal catching and pushing trajectories are planned for the underactuated system based on the virtual holonomic constraints approach. First experimental studies are presented to evaluate the approach.
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| 3. |
- Ericson, Stefan, et al.
(författare)
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Row-detection on an agricultural field using omnidirectional camera
- 2010
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Ingår i: 2010 IEEE/RSJ international conference on intelligent robots and systems. - Piscataway, N.J. : IEEE Press. - 9781424466740 - 9781424466764 - 9781424466757 ; , s. 4982-4987
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Konferensbidrag (refereegranskat)abstract
- This paper describes a method of detecting parallel rows on an agricultural field using an omnidirectional camera. The method works both on cameras with a fisheye lens and cameras with a catadioptric lens. A combination of an edge based method and a Hough transform method is suggested to find the rows. The vanishing point of several parallel rows is estimated using a second Hough transform. The method is evaluated on synthetic images generated with calibration data from real lenses. Scenes with several rows are produced, where each plant is positioned with a specified error. Experiments are performed on these synthetic images and on real field images. The result shows that good accuracy is obtained on the vanishing point once it is detected correctly. Further it shows that the edge based method works best when the rows consists of solid lines, and the Hough method works best when the rows consists of individual plants. The experiments also show that the combined method provides better detection than using the methods separately.
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| 4. |
- Johnson-Roberson, Matthew, et al.
(författare)
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Attention-based Active 3D Point Cloud Segmentation
- 2010
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Ingår i: IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010). - 9781424466757 ; , s. 1165-1170
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Konferensbidrag (refereegranskat)abstract
- In this paper we present a framework for the segmentation of multiple objects from a 3D point cloud. We extend traditional image segmentation techniques into a full 3D representation. The proposed technique relies on a state-of-the-art min-cut framework to perform a fully 3D global multi-class labeling in a principled manner. Thereby, we extend our previous work in which a single object was actively segmented from the background. We also examine several seeding methods to bootstrap the graphical model-based energy minimization and these methods are compared over challenging scenes. All results are generated on real-world data gathered with an active vision robotic head. We present quantitive results over aggregate sets as well as visual results on specific examples.
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| 5. |
- Krug, Robert, 1981-, et al.
(författare)
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On the efficient computation of independent contact regions for force closure grasps
- 2010
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Ingår i: IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems (IROS 2010). - : IEEE conference proceedings. - 9781424466757 ; , s. 586-591
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Since the introduction of independent contact regions in order to compensate for shortcomings in the positioning accuracy of robotic hands, alternative methods for their generation have been proposed. Due to the fact that (in general) such regions are not unique, the computation methods used usually reflect the envisioned application and/or underlying assumptions made. This paper introduces a parallelizable algorithm for the efficient computation of independent contact regions, under the assumption that a user input in the form of initial guess for the grasping points is readily available. The proposed approach works on discretized 3D-objects with any number of contacts and can be used with any of the following models: frictionless point contact, point contact with friction and soft finger contact. An example of the computation of independent contact regions comprising a non-trivial task wrench space is given.
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| 6. |
- Romero, Javier, et al.
(författare)
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Spatio-Temporal Modeling of Grasping Actions
- 2010
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Ingår i: IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010). - 9781424466757 ; , s. 2103-2108
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Konferensbidrag (refereegranskat)abstract
- Understanding the spatial dimensionality and temporal context of human hand actions can provide representations for programming grasping actions in robots and inspire design of new robotic and prosthetic hands. The natural representation of human hand motion has high dimensionality. For specific activities such as handling and grasping of objects, the commonly observed hand motions lie on a lower-dimensional non-linear manifold in hand posture space. Although full body human motion is well studied within Computer Vision and Biomechanics, there is very little work on the analysis of hand motion with nonlinear dimensionality reduction techniques. In this paper we use Gaussian Process Latent Variable Models (GPLVMs) to model the lower dimensional manifold of human hand motions during object grasping. We show how the technique can be used to embed high-dimensional grasping actions in a lower-dimensional space suitable for modeling, recognition and mapping.
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| 7. |
- Rubio, Oscar J., et al.
(författare)
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Representations for Object Grasping and Learning from Experience
- 2010
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Ingår i: IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010). - 9781424466757 ; , s. 1566-1571
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Konferensbidrag (refereegranskat)abstract
- We study two important problems in the area of robot grasping: i) the methodology and representations for grasp selection on known and unknown objects, and ii) learning from experience for grasping of similar objects. The core part of the paper is the study of different representations necessary for implementing grasping tasks on objects of different complexity. We show how to select a grasp satisfying force-closure, taking into account the parameters of the robot hand and collision-free paths. Our implementation takes also into account efficient computation at different levels of the system regarding representation, description and grasp hypotheses generation.
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| 8. |
- Sjöö, Kristoffer, et al.
(författare)
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Mechanical support as a spatial abstraction for mobile robots
- 2010
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Ingår i: IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010). - 9781424466757 ; , s. 4894-4900
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Konferensbidrag (refereegranskat)abstract
- Motivated by functional interpretations of spatial language terms, and the need for cognitively plausible and practical abstractions for mobile service robots, we present a spatial representation based on the physical support of one object by another, corresponding to the preposition "on". A perceptual model for evaluating this relation is suggested, and experiments-simulated as well as using a real robot -are presented. We indicate how this model can be used for important tasks such as communication of spatial knowledge, abstract reasoning and learning, taking as an example direct and indirect visual search. We also demonstrate the model experimentally and show that it produces intuitively feasible results from visual scene analysis as well as synthetic distributions that can be put to a number of uses.
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| 9. |
- Stoyanov, Todor, et al.
(författare)
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Path planning in 3D environments using the normal distributions transform
- 2010
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Ingår i: IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems (IROS 2010). - : IEEE conference proceedings. - 9781424466757 ; , s. 3263-3268
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Konferensbidrag (refereegranskat)abstract
- Planning feasible paths in fully three-dimensional environments is a challenging problem. Application of existing algorithms typically requires the use of limited 3D representations that discard potentially useful information. This article proposes a novel approach to path planning that utilizes a full 3D representation directly: the Three-Dimensional Normal Distributions Transform (3D-NDT). The well known wavefront planner is modified to use 3D-NDT as a basis for map representation and evaluated using both indoor and outdoor data sets. The use of 3D-NDT for path planning is thus demonstrated to be a viable choice with good expressive capabilities.
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| 10. |
- Zhou, Shengyan, et al.
(författare)
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Self-supervised learning method for unstructured road detection using Fuzzy Support Vector Machines
- 2010
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Ingår i: IROS 2010. - Piscataway : IEEE Press. - 9781424466757 ; , s. 1183-1189
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Konferensbidrag (refereegranskat)abstract
- Road detection is a crucial problem in the application of autonomous vehicle and on-road mobile robot. Most of the recent methods only achieve reliable results in some particular well-arranged environments. In this paper, we describe a road detection algorithm for front-view monocular camera using road probabilistic distribution model (RPDM) and online learning method. The primary contribution of this paper is that the combination of dynamical RPDM and Fuzzy Support Vector Machines (FSVMs) makes the algorithm being capable of self-supervised learning and optimized learning from the inheritance of previous result. The secondary contribution of this paper is that the proposed algorithm uses road geometrical assumption to extract assumption based misclassified points and retrains itself online which makes it easier to find potential misclassified points. Those points take an important role in online retraining the classifier which makes the algorithm adaptive to environment changing.
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