| 1. |
- Almqvist, Håkan, 1984-, et al.
(författare)
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Improving Point-Cloud Accuracy from a Moving Platform in Field Operations
- 2013
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Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE conference proceedings. - 9781467356411 - 9781467356435 ; , s. 733-738
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Konferensbidrag (refereegranskat)abstract
- This paper presents a method for improving the quality of distorted 3D point clouds made from a vehicle equipped with a laser scanner moving over uneven terrain. Existing methods that use 3D point-cloud data (for tasks such as mapping, localisation, and object detection) typically assume that each point cloud is accurate. For autonomous robots moving in rough terrain, it is often the case that the vehicle moves a substantial amount during the acquisition of one point cloud, in which case the data will be distorted. The method proposed in this paper is capable of increasing the accuracy of 3D point clouds, without assuming any specific features of the environment (such as planar walls), without resorting to a "stop-scan-go" approach, and without relying on specialised and expensive hardware. Each new point cloud is matched to the previous using normal-distribution-transform (NDT) registration, after which a mini-loop closure is performed with a local, per-scan, graph-based SLAM method. The proposed method increases the accuracy of both the measured platform trajectory and the point cloud. The method is validated on both real-world and simulated data.
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| 2. |
- Bekiroglu, Yasemin, et al.
(författare)
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A probabilistic framework for task-oriented grasp stability assessment
- 2013
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Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE Computer Society. - 1050-4729. - 9781467356411 ; , s. 3040-3047
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Konferensbidrag (refereegranskat)abstract
- We present a probabilistic framework for grasp modeling and stability assessment. The framework facilitates assessment of grasp success in a goal-oriented way, taking into account both geometric constraints for task affordances and stability requirements specific for a task. We integrate high-level task information introduced by a teacher in a supervised setting with low-level stability requirements acquired through a robot's self-exploration. The conditional relations between tasks and multiple sensory streams (vision, proprioception and tactile) are modeled using Bayesian networks. The generative modeling approach both allows prediction of grasp success, and provides insights into dependencies between variables and features relevant for object grasping.
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| 3. |
- Detry, Renaud, et al.
(författare)
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Learning a dictionary of prototypical grasp-predicting parts from grasping experience
- 2013
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Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA). - New York : IEEE. - 9781467356411 ; , s. 601-608
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Konferensbidrag (refereegranskat)abstract
- We present a real-world robotic agent that is capable of transferring grasping strategies across objects that share similar parts. The agent transfers grasps across objects by identifying, from examples provided by a teacher, parts by which objects are often grasped in a similar fashion. It then uses these parts to identify grasping points onto novel objects. We focus our report on the definition of a similarity measure that reflects whether the shapes of two parts resemble each other, and whether their associated grasps are applied near one another. We present an experiment in which our agent extracts five prototypical parts from thirty-two real-world grasp examples, and we demonstrate the applicability of the prototypical parts for grasping novel objects.
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| 4. |
- Guo, Meng, et al.
(författare)
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Revising motion planning under Linear Temporal Logic specifications in partially known workspaces
- 2013
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Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE Computer Society. - 9781467356411 - 9781467356435 ; , s. 5025-5032
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Konferensbidrag (refereegranskat)abstract
- In this paper we propose a generic framework for real-time motion planning based on model-checking and revision. The task specification is given as a Linear Temporal Logic formula over a finite abstraction of the robot motion. A preliminary motion plan is first generated based on the initial knowledge of the system model. Then real-time information obtained during the runtime is used to update the system model, verify and further revise the motion plan. The implementation and revision of the motion plan are performed in real-time. This framework can be applied to partially-known workspaces and workspaces with large uncertainties. Computer simulations are presented to demonstrate the efficiency of the framework.
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| 5. |
- Hjelm, Martin, 1980-, et al.
(författare)
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Sparse Summarization of Robotic Grasping Data
- 2013
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Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA). - New York : IEEE. - 9781467356435 - 9781467356411 ; , s. 1082-1087
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Konferensbidrag (refereegranskat)abstract
- We propose a new approach for learning a summarized representation of high dimensional continuous data. Our technique consists of a Bayesian non-parametric model capable of encoding high-dimensional data from complex distributions using a sparse summarization. Specifically, the method marries techniques from probabilistic dimensionality reduction and clustering. We apply the model to learn efficient representations of grasping data for two robotic scenarios.
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| 6. |
- Karayiannidis, Yiannis, 1980-, et al.
(författare)
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Model-free robot manipulation of doors and drawers by means of fixed-grasps
- 2013
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Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA). - New York : IEEE. - 9781467356411 ; , s. 4485-4492
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Konferensbidrag (refereegranskat)abstract
- This paper addresses the problem of robot interaction with objects attached to the environment through joints such as doors or drawers. We propose a methodology that requires no prior knowledge of the objects’ kinematics, including the type of joint - either prismatic or revolute. The method consists of a velocity controller which relies onforce/torque measurements and estimation of the motion direction,rotational axis and the distance from the center of rotation.The method is suitable for any velocity controlled manipulatorwith a force/torque sensor at the end-effector. The force/torquecontrol regulates the applied forces and torques within givenconstraints, while the velocity controller ensures that the endeffectormoves with a task-related desired tangential velocity. The paper also provides a proof that the estimates converge tothe actual values. The method is evaluated in different scenarios typically met in a household environment.
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| 7. |
- Kleiner, Alexander, et al.
(författare)
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Guaranteed Search With Large Teams of Unmanned Aerial Vehicles
- 2013
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Ingår i: Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA). - : IEEE conference proceedings. - 9781467356411 ; , s. 2977-2983
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Konferensbidrag (refereegranskat)abstract
- We consider the problem of detecting moving and evading targets by a team of coordinated unmanned aerial vehicles (UAVs) in large and complex 2D and 2.5D environments. Our approach is based on the coordination of 2D sweep lines that move through the environment to clear it from all contamination, representing the possibility of a target being located in an area, and thereby detecting all targets. The trajectories of the UAVs are implicitly given by the motion of these sweep lines and their costs are determined by the number of UAVs needed. A novel algorithm that computes low cost coordination strategies of the UAV sweep lines in simply connected polygonal environments is presented. The resulting strategies are then converted to strategies clearing multiply connected and 2.5D environments. Experiments on real and artificial elevation maps with complex visibility constraints are presented and demonstrate the feasibility and scalability of the approach. The algorithms used for the experiments are made available on a public repository.
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| 8. |
- Mosberger, Rafael, 1980-, et al.
(författare)
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An Inexpensive Monocular Vision System for Tracking Humans in Industrial Environments
- 2013
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Ingår i: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). - : IEEE conference proceedings. - 9781467356411 ; , s. 5850-5857
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Konferensbidrag (refereegranskat)abstract
- We report on a novel vision-based method for reliable human detection from vehicles operating in industrial environments in the vicinity of workers. By exploiting the fact that reflective vests represent a standard safety equipment on most industrial worksites, we use a single camera system and active IR illumination to detect humans by identifying the reflective vest markers. Adopting a sparse feature based approach, we classify vest markers against other reflective material and perform supervised learning of the object distance based on local image descriptors. The integration of the resulting per-feature 3D position estimates in a particle filter finally allows to perform human tracking in conditions ranging from broad daylight to complete darkness.
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| 9. |
- Nilsson, Jonas, 1979, et al.
(författare)
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Bundle adjustment using single-track vehicle model
- 2013
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Ingår i: Proceedings - IEEE International Conference on Robotics and Automation. - 1050-4729. - 9781467356411 ; , s. 2888-2893
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Konferensbidrag (refereegranskat)abstract
- This paper describes a method for estimating the 6-DoF viewing parameters of a calibrated vehicle-mounted camera. Visual features are combined with standard in-vehicle sensors and a single-track vehicle motion model in a bundle adjustment framework to produce a jointly optimal viewing parameter estimate. Results show that the vehicle motion model in combination with in-vehicle sensors exhibit good accuracy in estimating planar vehicle motion. This property is preserved, when combining these information sources with vision. Furthermore, the accuracy obtained from vision-only in direction estimation is not only maintained, but in fact further improved, primarily in situations where the matched visual features are few.
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| 10. |
- Patel, M., et al.
(författare)
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Language for learning complex human-object interactions
- 2013
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Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE Computer Society. - 9781467356411 ; , s. 4997-5002
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Konferensbidrag (refereegranskat)abstract
- In this paper we use a Hierarchical Hidden Markov Model (HHMM) to represent and learn complex activities/task performed by humans/robots in everyday life. Action primitives are used as a grammar to represent complex human behaviour and learn the interactions and behaviour of human/robots with different objects. The main contribution is the use of a probabilistic model capable of representing behaviours at multiple levels of abstraction to support the proposed hypothesis. The hierarchical nature of the model allows decomposition of the complex task into simple action primitives. The framework is evaluated with data collected for tasks of everyday importance performed by a human user.
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| 11. |
- Pieropan, Alessandro, et al.
(författare)
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Functional Object Descriptors for Human Activity Modeling
- 2013
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Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE conference proceedings. - 9781467356411 ; , s. 1282-1289
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Konferensbidrag (refereegranskat)abstract
- The ability to learn from human demonstration is essential for robots in human environments. The activity models that the robot builds from observation must take both the human motion and the objects involved into account. Object models designed for this purpose should reflect the role of the object in the activity - its function, or affordances. The main contribution of this paper is to represent object directly in terms of their interaction with human hands, rather than in terms of appearance. This enables the direct representation of object affordances/function, while being robust to intra-class differences in appearance. Object hypotheses are first extracted from a video sequence as tracks of associated image segments. The object hypotheses are encoded as strings, where the vocabulary corresponds to different types of interaction with human hands. The similarity between two such object descriptors can be measured using a string kernel. Experiments show these functional descriptors to capture differences and similarities in object affordances/function that are not represented by appearance.
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| 12. |
- Pokorny, Florian T., et al.
(författare)
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Grasping Objects with Holes : A Topological Approach
- 2013
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Ingår i: 2013 IEEE International Conference on Robotics and Automation (ICRA). - New York : IEEE. - 9781467356411 ; , s. 1100-1107
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 13. |
- Song, Dan, et al.
(författare)
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Predicting human intention in visual observations of hand/object interactions
- 2013
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Ingår i: 2013 IEEE International Conference On Robotics And Automation (ICRA). - New York : IEEE. - 9781467356435 - 9781467356411 ; , s. 1608-1615
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Konferensbidrag (refereegranskat)abstract
- The main contribution of this paper is a probabilistic method for predicting human manipulation intention from image sequences of human-object interaction. Predicting intention amounts to inferring the imminent manipulation task when human hand is observed to have stably grasped the object. Inference is performed by means of a probabilistic graphical model that encodes object grasping tasks over the 3D state of the observed scene. The 3D state is extracted from RGB-D image sequences by a novel vision-based, markerless hand-object 3D tracking framework. To deal with the high-dimensional state-space and mixed data types (discrete and continuous) involved in grasping tasks, we introduce a generative vector quantization method using mixture models and self-organizing maps. This yields a compact model for encoding of grasping actions, able of handling uncertain and partial sensory data. Experimentation showed that the model trained on simulated data can provide a potent basis for accurate goal-inference with partial and noisy observations of actual real-world demonstrations. We also show a grasp selection process, guided by the inferred human intention, to illustrate the use of the system for goal-directed grasp imitation.
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| 14. |
- Wigström, Oskar, 1986, et al.
(författare)
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Sustainable production automation - Energy optimization of robot cells
- 2013
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Ingår i: Proceedings - IEEE International Conference on Robotics and Automation. - 1050-4729. - 9781467356411 ; , s. 252-257
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Konferensbidrag (refereegranskat)abstract
- This paper concerns the reduction of energy use in manufacturing industry. If individual robot movements in a system are preprocessed using Dynamic Programming, one can attain a Mixed Integer Nonlinear Program (MINLP) which models the energy consumption of the complete system. This model can then be solved to optimality using mathematical programming. We have previously shown proof of concept for this energy reduction method. In this paper, we apply state of the art MINLP methods to a number of problems in order benchmark their effectiveness. Algorithms used are Nonlinear Programming based Branch and Bound (NLP-BB), Outer Approximation (OA), LP/NLP based Branch and Bound (LP/NLP-BB) and Extended Cutting Plane (ECP). Benchmarks show that the NLP-BB does not perform well for nonlinear scheduling problems. This is due to the weak lower bounds of the integer relaxations. For scheduling problems with nonlinear costs, ECP and in particular LP/NLP-BB are shown to outperform both NLP-BB and OA. The resulting energy optimal schedules for the examples show a significant decrease in energy consumption.
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