| 1. |
- Ambrus, Rares, et al.
(författare)
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Unsupervised learning of spatial-temporal models of objects in a long-term autonomy scenario
- 2015
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Ingår i: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781479999941 ; , s. 5678-5685
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Konferensbidrag (refereegranskat)abstract
- We present a novel method for clustering segmented dynamic parts of indoor RGB-D scenes across repeated observations by performing an analysis of their spatial-temporal distributions. We segment areas of interest in the scene using scene differencing for change detection. We extend the Meta-Room method and evaluate the performance on a complex dataset acquired autonomously by a mobile robot over a period of 30 days. We use an initial clustering method to group the segmented parts based on appearance and shape, and we further combine the clusters we obtain by analyzing their spatial-temporal behaviors. We show that using the spatial-temporal information further increases the matching accuracy.
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| 2. |
- Caccamo, Sergio, et al.
(författare)
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Extending a UGV Teleoperation FLC Interface with Wireless Network Connectivity Information
- 2015
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Ingår i: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781479999941 ; , s. 4305-4312
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Konferensbidrag (refereegranskat)abstract
- Teleoperated Unmanned Ground Vehicles (UGVs) are expected to play an important role in future search and rescue operations. In such tasks, two factors are crucial for a successful mission completion: operator situational awareness and robust network connectivity between operator and UGV. In this paper, we address both these factors by extending a new Free Look Control (FLC) operator interface with a graphical representation of the Radio Signal Strength (RSS) gradient at the UGV location. We also provide a new way of estimating this gradient using multiple receivers with directional antennas. The proposed approach allows the operator to stay focused on the video stream providing the crucial situational awareness, while controlling the UGV to complete the mission without moving into areas with dangerously low wireless connectivity. The approach is implemented on a KUKA youBot using commercial-off-the-shelf components. We provide experimental results showing how the proposed RSS gradient estimation method performs better than a difference approximation using omnidirectional antennas and verify that it is indeed useful for predicting the RSS development along a UGV trajectory. We also evaluate the proposed combined approach in terms of accuracy, precision, sensitivity and specificity.
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| 3. |
- Droukas, Leonidas, et al.
(författare)
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Force/Position/Rolling Control For Spherical Tip Robotic Fingers
- 2015
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Ingår i: IEEE International Conference on Intelligent Robots and Systems. - 2153-0858 .- 2153-0866. - 9781479999941 ; 2015-December, s. 858-863
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Konferensbidrag (refereegranskat)abstract
- The rolling motion of a soft robotic fingertip is in this paper explicitly included in the control objectives together with the force/position regulation targets. A model based control law is proposed to linearize and decouple the system with respect to the force/position and sliding dynamics based on an appropriately defined task Jacobian. The controller is validated by simulations including rolling on a stationary surface and graspless manipulation of a flat object.
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| 4. |
- Ghadirzadeh, Ali, 1987-, et al.
(författare)
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A Sensorimotor Approach for Self-Learning of Hand-Eye Coordination
- 2015
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Ingår i: IEEE/RSJ International Conference onIntelligent Robots and Systems, Hamburg, September 28 - October 02, 2015. - : IEEE conference proceedings. - 9781479999941 ; , s. 4969-4975
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Konferensbidrag (refereegranskat)abstract
- This paper presents a sensorimotor contingencies (SMC) based method to fully autonomously learn to perform hand-eye coordination. We divide the task into two visuomotor subtasks, visual fixation and reaching, and implement these on a PR2 robot assuming no prior information on its kinematic model. Our contributions are three-fold: i) grounding a robot in the environment by exploiting SMCs in the action planning system, which eliminates the need for prior knowledge of the kinematic or dynamic models of the robot; ii) using a forward model to search for proper actions to solve the task by minimizing a cost function, instead of training a separate inverse model, to speed up training; iii) encoding 3D spatial positions of a target object based on the robot’s joint positions, thus avoiding calibration with respect to an external coordinate system. The method is capable of learning the task of hand-eye coordination from scratch by less than 20 sensory-motor pairs that are iteratively generated at real-time speed. In order to examine the robustness of the method while dealing with nonlinear image distortions, we apply a so-called retinal mapping image deformation to the input images. Experimental results show the successfulness of the method even under considerable image deformations.
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| 5. |
- Lowry, Stephanie, 1979-, et al.
(författare)
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Building Beliefs : Unsupervised Generation of Observation Likelihoods for Probabilistic Localization in Changing Environments
- 2015
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Ingår i: IEEE International Conference on Intelligent Robots and Systems (IROS), IEEE, 2015. - New York, USA : IEEE. - 9781479999941 ; , s. 3071-3078
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Konferensbidrag (refereegranskat)abstract
- This paper is concerned with the interpretation of visual information for robot localization. It presents a probabilistic localization system that generates an appropriate observation model online, unlike existing systems which require pre-determined belief models. This paper proposes that probabilistic visual localization requires two major operating modes - one to match locations under similar conditions and the other to match locations under different conditions. We develop dual observation likelihood models to suit these two different states, along with a similarity measure-based method that identifies the current conditions and switches between the models. The system is experimentally tested against different types of ongoing appearance change. The results demonstrate that the system is compatible with a wide range of visual front-ends, and the dual-model system outperforms a single-model or pre-trained approach and state-of-the-art localization techniques.
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| 6. |
- Mojtahedzadeh, Rasoul, 1977-, et al.
(författare)
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A principle of minimum translation search approach for object pose refinement
- 2015
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Ingår i: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - : IEEE Press. - 9781479999941 ; , s. 2897-2903
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Konferensbidrag (refereegranskat)abstract
- The state-of-the-art object pose estimation approaches represent the set of detected poses together with corresponding uncertainty. The inaccurate noisy poses may result in a configuration of overlapping objects especially in cluttered environments. Under a rigid body assumption the inter-penetrations between pairs of objects are geometrically inconsistent. In this paper, we propose the principle of minimum translation search, PROMTS, to find an inter-penetration-free configuration of the initially detected objects. The target application is to automate the task of unloading shipping containers, where a geometrically consistent configuration of objects is required for high level reasoning and manipulation. We find that the proposed approach to resolve geometrical inconsistencies improves the overall pose estimation accuracy. We examine the utility of two selected search methods: A-star and Depth-Limited search. The performance of the search algorithms are tested on data sets generated in simulation and from real-world scenarios. The results show overall improvement of the estimated poses and suggest that depth-limited search presents the best overall performance.
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| 7. |
- Pauwels, Karl, et al.
(författare)
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SimTrack : A Simulation-based Framework for Scalable Real-time Object Pose Detection and Tracking
- 2015
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Ingår i: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781479999941 ; , s. 1300-1307
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Konferensbidrag (refereegranskat)abstract
- We propose a novel approach for real-time object pose detection and tracking that is highly scalable in terms of the number of objects tracked and the number of cameras observing the scene. Key to this scalability is a high degree of parallelism in the algorithms employed. The method maintains a single 3D simulated model of the scene consisting of multiple objects together with a robot operating on them. This allows for rapid synthesis of appearance, depth, and occlusion information from each camera viewpoint. This information is used both for updating the pose estimates and for extracting the low-level visual cues. The visual cues obtained from each camera are efficiently fused back into the single consistent scene representation using a constrained optimization method. The centralized scene representation, together with the reliability measures it enables, simplify the interaction between pose tracking and pose detection across multiple cameras. We demonstrate the robustness of our approach in a realistic manipulation scenario. We publicly release this work as a part of a general ROS software framework for real-time pose estimation, SimTrack, that can be integrated easily for different robotic applications.
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| 8. |
- Pinggera, Peter, et al.
(författare)
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High-Performance Long Range Obstacle Detection Using Stereo Vision
- 2015
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Ingår i: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781479999941 ; , s. 1308-1313
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Konferensbidrag (refereegranskat)abstract
- Reliable detection of obstacles at long range is crucial for the timely response to hazards by fast-moving safety-critical platforms like autonomous cars. We present a novel method for the joint detection and localization of distant obstacles using a stereo vision system on a moving platform. The approach is applicable to both static and moving obstacles and pushes the limits of detection performance as well as localization accuracy. The proposed detection algorithm is based on sound statistical tests using local geometric criteria which implicitly consider non-flat ground surfaces. To achieve maximum performance, it operates directly on image data instead of precomputed stereo disparity maps. A careful experimental evaluation on several datasets shows excellent detection performance and localization accuracy up to very large distances, even for small obstacles. We demonstrate a parallel implementation of the proposed system on a GPU that executes at real-time speeds.
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| 9. |
- Raman, Vasumathi, et al.
(författare)
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Online Horizon Selection in Receding Horizon Temporal Logic Planning
- 2015
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Ingår i: , 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - 9781479999941 ; , s. 3493-3499
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Konferensbidrag (refereegranskat)abstract
- Temporal logics have proven effective for correct-by-construction synthesis of controllers for a wide range of robotic applications. Receding horizon frameworks mitigate the computational intractability of reactive synthesis for temporal logic, but have thus far been limited by pursuing a single sequence of short horizon problems to the goal. We propose a receding horizon algorithm for reactive synthesis that automatically determines a path to the currently pursued goal at runtime, responding as needed to nondeterministic environment behavior. This is achieved by allowing each short horizon to have multiple local goals, and determining which local goal to pursue based on the current global goal, the currently perceived environment and a pre-computed invariant dependent on the global goal. We demonstrate the utility of this additional flexibility in grant-response tasks, using a search-and-rescue example. Moreover, we show that these goal-dependent invariants mitigate the conservativeness of the receding horizon approach.
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| 10. |
- Rockel, Sebastian, et al.
(författare)
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Integrating physics-based prediction with semantic plan execution monitoring
- 2015
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Ingår i: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781479999941 ; , s. 2883-2888
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Konferensbidrag (refereegranskat)abstract
- Real-world robotic systems have to deal with uncertain and dynamic environments to reliably perform tasks. State-of-the-art cognitive robotic systems use an abstract symbolic representation of the real world that is used for high level reasoning. Some aspects of the world, such as object dynamics, are inherently difficult to capture in an abstract symbolic form, yet they influence whether the executed action will succeed or fail. This paper presents an integrated system that uses a physics-based simulation for predicting robot action results and durations, combined with a Hierarchical Task Network (HTN) planner and semantic execution monitoring. We describe a fully integrated system performing functional imagination, which is essentially contributed by a Semantic Execution Monitor (SEM). Based on information obtained from functional imagination, the robot control decides whether it is necessary to adapt the plan that is currently being executed. As a proof of concept, we demonstrate PR2 able of carrying objects on a tray without the objects toppling. Our approach achieves this by considering the robot and object dynamics in simulation. A validation shows that robot action results in simulation can be transferred to the real world. The system improves on state-of-the-art AI plan-based systems by feeding simulated prediction results back into the execution system.
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| 11. |
- Stock, Sebastian, et al.
(författare)
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Online task merging with a hierarchical hybrid task planner for mobile service robots
- 2015
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Ingår i: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - New York : IEEE. - 9781479999941 ; , s. 6459-6464
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Konferensbidrag (refereegranskat)abstract
- Plan-based robot control has to consider a multitude of aspects of tasks at once, such as task dependency, time, space, and resource usage. Hybrid planning is a strategy for treating them jointly. However, by incorporating all these aspects into a hybrid planner, its search space is huge by construction. This paper introduces the planner CHIMP, which is based on meta-CSP planning to represent the hybrid plan space and uses hierarchical planning as the strategy for cutting efficiently through this space. The paper makes two contributions: First, it describes how HTN planning is integrated into meta-CSP reasoning leading to a planner that can reason about different forms of knowledge and that is fast enough to be used on a robot. Second, it demonstrates CHIMP’s task merging capabilities, i.e., the unification of different tasks from different plan parts, resulting in plans that are more efficient to execute. It also allows to merge new tasks online into a plan that is being executed. This is demonstrated on a PR2 robot.
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| 12. |
- Stork, Johannes Andreas, 1986-, et al.
(författare)
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Learning Predictive State Representations for planning
- 2015
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Ingår i: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - : IEEE Press. - 9781479999941 ; , s. 3427-3434
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Konferensbidrag (refereegranskat)abstract
- Predictive State Representations (PSRs) allow modeling of dynamical systems directly in observables and without relying on latent variable representations. A problem that arises from learning PSRs is that it is often hard to attribute semantic meaning to the learned representation. This makes generalization and planning in PSRs challenging. In this paper, we extend PSRs and introduce the notion of PSRs that include prior information (P-PSRs) to learn representations which are suitable for planning and interpretation. By learning a low-dimensional embedding of test features we map belief points of similar semantic to the same region of a subspace. This facilitates better generalization for planning and semantical interpretation of the learned representation. In specific, we show how to overcome the training sample bias and introduce feature selection such that the resulting representation emphasizes observables related to the planning task. We show that our P-PSRs result in qualitatively meaningful representations and present quantitative results that indicate improved suitability for planning.
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| 13. |
- Tsiamis, Anastasios, et al.
(författare)
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Decentralized Leader-Follower Control under High Level Goals without Explicit Communication
- 2015
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Ingår i: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS). - : IEEE. - 9781479999941 ; , s. 5790-5795
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Konferensbidrag (refereegranskat)abstract
- In this paper, we study the decentralized control problem of a two-agent system under local goal specifications given as temporal logic formulas. The agents collaboratively carry an object in a leader-follower scheme and lack means to exchange messages on-line, i. e., to communicate explicitly. Specifically, we propose a decentralized control protocol and a leader re-election strategy that secure the accomplishment of both agents' local goal specifications. The challenge herein lies in exploiting exclusively implicit inter- robot communication that is a natural outcome of the physical interaction of the robots with the object. An illustrative experiment is included clarifying and verifying the approach.
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| 14. |
- Vina, Francisco, 1990-, et al.
(författare)
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In-hand manipulation using gravity and controlled slip
- 2015
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Ingår i: Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on. - : IEEE conference proceedings. ; 2015-December, s. 5636-5641
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Konferensbidrag (refereegranskat)abstract
- In this work we propose a sliding mode controllerfor in-hand manipulation that repositions a tool in the robot’shand by using gravity and controlling the slippage of the tool. In our approach, the robot holds the tool with a pinch graspand we model the system as a link attached to the grippervia a passive revolute joint with friction, i.e., the grasp onlyaffords rotational motions of the tool around a given axis ofrotation. The robot controls the slippage by varying the openingbetween the fingers in order to allow the tool to move tothe desired angular position following a reference trajectory.We show experimentally how the proposed controller achievesconvergence to the desired tool orientation under variations ofthe tool’s inertial parameters.
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