| 1. |
- Andreasson, Henrik, 1977-, et al.
(författare)
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Real time registration of RGB-D data using local visual features and 3D-NDT registration
- 2012
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Ingår i: Proc. of International Conference on Robotics and Automation (ICRA) Workshop on Semantic Perception, Mapping and Exploration (SPME). - : IEEE. - 9781467314039
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Konferensbidrag (refereegranskat)abstract
- Recent increased popularity of RGB-D capable sensors in robotics has resulted in a surge of related RGBD registration methods. This paper presents several RGB-D registration algorithms based on combinations between local visual feature and geometric registration. Fast and accurate transformation refinement is obtained by using a recently proposed geometric registration algorithm, based on the Three-Dimensional Normal Distributions Transform (3D-NDT). Results obtained on standard data sets have demonstrated mean translational errors on the order of 1 cm and rotational errors bellow 1 degree, at frame processing rates of about 15 Hz.
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| 2. |
- Axelsson, Patrik, 1985-, et al.
(författare)
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Tool Position Estimation of a Flexible Industrial Robot using Recursive Bayesian Methods
- 2012
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Ingår i: Proceedings of the 2012 IEEE International Conference on Robotics and Automation. - 9781467314039 - 9781467314046 ; , s. 5234-5239
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Konferensbidrag (refereegranskat)abstract
- A sensor fusion method for state estimation of a flexible industrial robot is presented. By measuring the acceleration at the end-effector, the accuracy of the arm angular position is improved significantly when these measurements are fused with motor angle observation. The problem is formulated in a Bayesian estimation framework and two solutions are proposed; one using the extended Kalman filter (EKF) and one using the particle filter (PF). The technique is verified on experiments on the ABB IRB4600 robot, where the accelerometer method is showing a significant better dynamic performance, even when model errors are present.
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| 3. |
- Charusta, Krzysztof, 1983-, et al.
(författare)
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Generation of independent contact regions on objects reconstructed from noisy real-world range data
- 2012
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Ingår i: 2012 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE conference proceedings. - 9781467314053 - 9781467314039 ; , s. 1338-1344
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Konferensbidrag (refereegranskat)abstract
- The synthesis and evaluation of multi-fingered grasps on complex objects is a challenging problem that has received much attention in the robotics community. Although several promising approaches have been developed, applications to real-world systems are limited to simple objects or gripper configurations. The paradigm of Independent Contact Regions (ICRs) has been proposed as a way to increase the tolerance to grasp positioning errors. This concept is well established, though only on precise geometric object models. This work is concerned with the application of the ICR paradigm to models reconstructed from real-world range data. We propose a method for increasing the robustness of grasp synthesis on uncertain geometric models. The sensitivity of the ICR algorithm to noisy data is evaluated and a filtering approach is proposed to improve the quality of the final result.
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| 4. |
- Charusta, Krzysztof, 1983-, et al.
(författare)
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Independent contact regions based on a patch contact model
- 2012
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Ingår i: 2012 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE conference proceedings. - 9781467314053 - 9781467314039 ; , s. 4162-4169
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Konferensbidrag (refereegranskat)abstract
- The synthesis of multi-fingered grasps on nontrivial objects requires a realistic representation of the contact between the fingers of a robotic hand and an object. In this work, we use a patch contact model to approximate the contact between a rigid object and a deformable anthropomorphic finger. This contact model is utilized in the computation of Independent Contact Regions (ICRs) that have been proposed as a way to compensate for shortcomings in the finger positioning accuracy of robotic grasping devices. We extend the ICR algorithm to account for the patch contact model and show the benefits of this solution.
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| 5. |
- Cheng, N. G., et al.
(författare)
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Design and Analysis of a Robust, Low-cost, Highly Articulated manipulator enabled by jamming of granular media
- 2012
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Ingår i: Robotics and Automation (ICRA), 2012 IEEE International Conference on. - 9781467314039 ; , s. 4328-4333
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Konferensbidrag (refereegranskat)abstract
- Hyper-redundant manipulators can be fragile, expensive, and limited in their flexibility due to the distributed and bulky actuators that are typically used to achieve the precision and degrees of freedom (DOFs) required. Here, a manipulator is proposed that is robust, high-force, low-cost, and highly articulated without employing traditional actuators mounted at the manipulator joints. Rather, local tunable stiffness is coupled with off-board spooler motors and tension cables to achieve complex manipulator configurations. Tunable stiffness is achieved by reversible jamming of granular media, which - by applying a vacuum to enclosed grains - causes the grains to transition between solid-like states and liquid-like ones. Experimental studies were conducted to identify grains with high strength-to-weight performance. A prototype of the manipulator is presented with performance analysis, with emphasis on speed, strength, and articulation. This novel design for a manipulator - and use of jamming for robotic applications in general - could greatly benefit applications such as human-safe robotics and systems in which robots need to exhibit high flexibility to conform to their environments. © 2012 IEEE.
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| 6. |
- Detry, Renaud, et al.
(författare)
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Generalizing grasps across partly similar objects
- 2012
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Ingår i: 2012 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE Computer Society. - 9781467314039 ; , s. 3791-3797
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 7. |
- Madry, Marianna, et al.
(författare)
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From object categories to grasp transfer using probabilistic reasoning
- 2012
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Ingår i: 2012 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE Computer Society. - 9781467314039 ; , s. 1716-1723
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Konferensbidrag (refereegranskat)abstract
- In this paper we address the problem of grasp generation and grasp transfer between objects using categorical knowledge. The system is built upon an i) active scene segmentation module, able of generating object hypotheses and segmenting them from the background in real time, ii) object categorization system using integration of 2D and 3D cues, and iii) probabilistic grasp reasoning system. Individual object hypotheses are first generated, categorized and then used as the input to a grasp generation and transfer system that encodes task, object and action properties. The experimental evaluation compares individual 2D and 3D categorization approaches with the integrated system, and it demonstrates the usefulness of the categorization in task-based grasping and grasp transfer.
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| 8. |
- Pronobis, Andrzej, et al.
(författare)
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Large-scale semantic mapping and reasoning with heterogeneous modalities
- 2012
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Ingår i: 2012 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE Computer Society. - 9781467314039 ; , s. 3515-3522
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Konferensbidrag (refereegranskat)abstract
- This paper presents a probabilistic framework combining heterogeneous, uncertain, information such as object observations, shape, size, appearance of rooms and human input for semantic mapping. It abstracts multi-modal sensory information and integrates it with conceptual common-sense knowledge in a fully probabilistic fashion. It relies on the concept of spatial properties which make the semantic map more descriptive, and the system more scalable and better adapted for human interaction. A probabilistic graphical model, a chaingraph, is used to represent the conceptual information and perform spatial reasoning. Experimental results from online system tests in a large unstructured office environment highlight the system's ability to infer semantic room categories, predict existence of objects and values of other spatial properties as well as reason about unexplored space.
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| 9. |
- Song, Meng, et al.
(författare)
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Natural landmark extraction in cluttered forested environments
- 2012
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Ingår i: Proceedings - IEEE International Conference on Robotics and Automation. - Piscataway, N.J. : IEEE Press. - 9781467314039 ; , s. 4836-4843
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Konferensbidrag (refereegranskat)abstract
- In this paper, a new systematical method for extracting tree trunk landmarks from 3D point clouds of cluttered forested environments is proposed. This purely geometric method is established on scene understanding and automatic analysis of trees. The pipeline of our method includes three steps. First, the raw point clouds are segmented by utilizing the circular shape of trees, and segments are grouped into tree sections based on the principle of spatial proximity. Second, circles and axes are extracted from tree sections which are subject to loss of shape information. Third, by clustering and integrating the tree sections resulted from various space inconsistencies, straight tree trunk landmarks are finally formed for future localization. The experimental results from real forested environments are presented. © 2012 IEEE.
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| 10. |
- Stolt, Andreas, et al.
(författare)
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Force Controlled Robotic Assembly without a Force Sensor
- 2012
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Ingår i: IEEE International Conference on Robotics and Automation (ICRA), 2012. - 1050-4729 .- 2152-4092. - 9781467314039 ; , s. 1538-1543
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Konferensbidrag (refereegranskat)abstract
- The traditional way of controlling an industrial robot is to program it to follow desired trajectories. This approach is sufficient as long as the accuracy of the robot and the calibration of the workcell is good enough. In robotic assembly these conditions are usually not fulfilled, because of uncertainties, e.g., variability in involved parts and objects not gripped accurately. Using force control is one way to handle these difficulties. This paper presents a method of doing force control without a force sensor. The method is based on detuning of the low-level joint control loops, and the force is estimated from the control error. It is experimentally verified in a small part assembly task with a kinematically redundant robotic manipulator.
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| 11. |
- Stoyanov, Todor, 1984-, et al.
(författare)
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Point Set Registration through Minimization of the L-2 Distance between 3D-NDT Models
- 2012
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Ingår i: 2012 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE conference proceedings. - 9781467314053 - 9781467314039 ; , s. 5196-5201
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Konferensbidrag (refereegranskat)abstract
- Point set registration — the task of finding the best fitting alignment between two sets of point samples, is an important problem in mobile robotics. This article proposes a novel registration algorithm, based on the distance between Three- Dimensional Normal Distributions Transforms. 3D-NDT models — a sub-class of Gaussian Mixture Models with uniformly weighted, largely disjoint components, can be quickly computed from range point data. The proposed algorithm constructs 3DNDT representations of the input point sets and then formulates an objective function based on the L2 distance between the considered models. Analytic first and second order derivatives of the objective function are computed and used in a standard Newton method optimization scheme, to obtain the best-fitting transformation. The proposed algorithm is evaluated and shown to be more accurate and faster, compared to a state of the art implementation of the Iterative Closest Point and 3D-NDT Point-to-Distribution algorithms.
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