max planck institute autonomous motion

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Motion-based Object Segmentation based on Dense RGB-D Scene Flow Precision is achieved by modeling and correcting biases in the joint measurements as well as inaccuracies in the robot model, such as poor extrinsic camera calibration. arXiv code and dataset DOI Project Page Project Page Representatives The Max Planck Society is legally represented by its Board of Directors which, in turn, is represented by the President of the Society, Prof. Dr. Martin Stratmann and by Secretary General Rüdiger Willems. The Max-Planck-Institute for Intelligent System, and in particular the Autonomous Motion Department, is always looking for outstanding research talents on the Ph.D. student, postdoctoral, and research scientist level. Memristor-enhanced humanoid robot control system–Part I: theory behind the novel memcomputing paradigm code Here, we introduce a computationally efficient online meta-learning algorithm that builds and optimizes a memory model of the optimal learning rate landscape from previously observed gradient behaviors. Share, Büchler, D., Guist, S., Calandra, R., Berenz, V., Schölkopf, B., Peters, J. A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models pdf We argue that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets Share, Kloss, A., Bauza, M., Wu, J., Tenenbaum, J. IEEE Transactions on Robotics, 33, pages: 1273-1291, December 2017 (article), arXiv On this basis, we outline some conditions which potential generalizations have to satisfy in order to maintain the computational efficiency of the GF. B. PDF In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 5776-5782, IEEE, Brisbane, Australia, 2018 (inproceedings). In this work, we present an extension to a linear Model Predictive Control (MPC) scheme that plans external contact forces for the robot when given multiple contact locations and their corresponding friction cone. It enables safe and robust decision-making under the large uncertainty of the real-world. In task-based inverse dynamics control, reference accelerations used to follow a desired plan can be broken down into feedforward and feedback trajectories. link (url) Garcia Cifuentes, C., Issac, J., Wüthrich, M., Schaal, S., Bohg, J. arXiv Marco, A., Rohr, A. V., Baumann, D., Hernández-Lobato, J. M., Trimpe, S. arXiv Our approach emphasizes the importance of continuous, real-time perception and its tight integration with reactive motion generation methods. A New Perspective and Extension of the Gaussian Filter link (url) DOI Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems. In 333 experiments, we show the robustness and accuracy of the proposed system. Doerr, A., Nguyen-Tuong, D., Marco, A., Schaal, S., Trimpe, S. PDF Share, Doerr, A., Daniel, C., Schiegg, M., Nguyen-Tuong, D., Schaal, S., Toussaint, M., Trimpe, S. IEEE Robotics and Automation Letters, 3(4):3797-3804, IEEE, IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2018 (conference), Project Page A New Data Source for Inverse Dynamics Learning I am PhD student at the Max Planck Institute for Intelligent Systems and ETH Zurich as part of the Max Planck ETH Center for Learning Systems program. linear and nonlinear systems demonstrate that the LQR kernels yield superior code and dataset Robots | Autonomous Motion - Max Planck Institute for Intelligent Systems. We seek to develop fundamental methods and algorithms that enable robots and other intelligent systems to interact with their environment through feedback, autonomously … In our previous work, we proposed a convex relaxation of the problem that allowed to efficiently compute momentum trajectories and contact forces. In our model, we propose to use the first and second order moments of the object occupancy function to represent an object instance. represent the learned behavior as a set of associations between Recursive Bayesian Filtering algorithms address the state estimation problem, but they require models of process dynamics and sensory observations as well as noise characteristics of these models. Max Planck Institute for Intelligent Systems. PDF In this paper, we show how to reduce the required contribution of the feedback controller by incorporating learned task-space reference accelerations. Optimizing contact locations while taking dynamics into account is computationally costly and in only partially observed environments, executing contact-based tasks often suffers from low accuracy. [BibTex]. DOI Heijmink, E., Radulescu, A., Ponton, B., Barasuol, V., Caldwell, D., Semini, C. paper The NN is trained and validated from offline samples of the MPC, yielding statistical guarantees, and used in lieu thereof at run time. The International Journal of Robotics Research, 35(14):1731-1749, December 2016 (article), PDF Noticing that the non-convexity introduced by the time variables is of similar nature as the centroidal dynamics one, we propose two convex relaxations to the problem based on trust regions and soft constraints. Share, Sutanto, G., Ratliff, N., Sundaralingam, B., Chebotar, Y., Su, Z., Handa, A., Fox, D. Our group investigates novel methods for learning the basic physical 3D understanding of dynamic environments up to complex tasks such as autonomous … Project Page Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 411-417, IEEE, Brisbane, Australia, 2018 (inproceedings). Given such a consensus, particular cases of ethical dilemmas where ethicists agree on the ethically relevant features and the right course of action can be used to help discover principles that balance these features when they are in conflict. Quantitative and qualitative results show the complexity of the prediction problem. In Proceedings of the IEEE/RSJ International Conference of Intelligent Robots and Systems, September 2017 (inproceedings) Accepted, Project Page Probabilistic Articulated Real-Time Tracking for Robot Manipulation Project Page On underactuated, free-floating robots, such as humanoids, high feedback terms can be used to improve tracking accuracy; however, this can lead to very stiff behavior or poor tracking accuracy due to limited control bandwidth. We implement DFs with four different underlying filtering algorithms and compare them in extensive experiments. Grossberger, L., Hohmann, M. R., Peters, J., Grosse-Wentrup, M. Grossberger, L., Hohmann, M. R., Peters, J., Grosse-Wentrup, M. Share, Arslan, Ö. video Learning Sensory-Motor Associations from Demonstration We propose a probabilistic filtering method which fuses joint measurements with depth images to yield a precise, real-time estimate of the end-effector pose in the camera frame. Nevertheless, we show that this small change can have a major impact on the estimation accuracy. In this paper we present a methodology for improving the performance of a trotting gait by learning the gait parameters, impedance profile and the gains of the control architecture. Share, Merzic, H., Bogdanovic, M., Kappler, D., Righetti, L., Bohg, J. Project Page arXiv Bohg, J., Hausman, K., Sankaran, B., Brock, O., Kragic, D., Schaal, S., Sukhatme, G. arXiv The Max Planck Institute for Intelligent Systems has campuses in Stuttgart and Tübingen. In the first optimization, we compute the Center of Mass (CoM) trajectory, foot step locations, and introduce slack variables to account for violating the imposed constraints on the Zero Moment Point (ZMP). In contrast to prior work, our policies show better generalization across different goals. Ömür Arslan is currently a research scientist in the Autonomous Motion Department at the Max Planck Institute for Intelligent Systems (MPI-IS). arXiv Recent approaches in robotics follow the insight that perception is facilitated by interactivity with the environment. [BibTex] Recently, the centroidal momentum dynamics has received substantial attention to plan dynamically consistent motions for robots with arms and legs in multi-contact scenarios. Marco, A., Berkenkamp, F., Hennig, P., Schoellig, A. P., Krause, A., Schaal, S., Trimpe, S. PDF As is shown herein, GPs with a common kernel choice can, DOI [BibTex], Shao, L., Tian, Y., Bohg, J. [BibTex] The successful execution of complex modern robotic tasks often relies on the correct tuning of a large number of parameters. Project Page For selecting Learning Sensor Feedback Models from Demonstrations via Phase-Modulated Neural Networks However, developing software suitable for dynamic environments is difficult. We propose to use a convolutional neural network to convert raw depth images or organized point clouds into a suitable representation for the analytical model and compare this approach to using neural networks for both, perception and prediction. Project Page We present a fully integrated system where real-time object and robot tracking as well as ambient world modeling provides the necessary input to feedback controllers and continuous motion optimizers. [BibTex]. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2019, IEEE, International Conference on Robotics and Automation, May 2019 (inproceedings) Accepted, pdf Thereby, we hope to define a field and inspire future work. [BibTex] We present an approach that achieves both by combining novel robust model predictive control (MPC) with function approximation via (deep) neural networks (NNs). Local Bayesian Optimization of Motor Skills B., Rodriguez, A., Bohg, J. Recently, Bayesian optimization (BO) has been proposed as a powerful DOI Multiple distributed sensor agents observe a dynamic process and sporadically transmit their measurements to estimator agents over a shared bus network. link (url) DOI This allows us to Share, Meier, F., Kappler, D., Schaal, S. Wang, Z., Boularias, A., Mülling, K., Schölkopf, B., Peters, J. DOI This clustering-based contact probability estimator is validated in a kinematics-based base state estimator in a simulation environment with realistic added sensor noise for locomotion over rough, low-friction terrain on which the robot is subject to foot slip and rotation. Recently, multiple works have demonstrated that these models can be learned by end-to-end training through differentiable versions of Recursive Filtering algorithms.The aim of this work is to improve understanding and applicability of such differentiable filters (DF). DOI Empirical validation shows that our algorithm uses the failures budget more efficiently in a variety of optimization experiments, and generally achieves lower regret, than state-of-the-art methods. The data required for training is solely from proprioceptive sensors - endeffector contact wrench sensors and inertial measurement units (IMUs) - and the method is completely unsupervised. He was also an Invited Researcher at the ATR Computational Neuroscience Laboratory in Japan, where he held an appointment as Head of the Computational Learning Group during an international ERATO project, the Kawato Dynamic Brain … To achieve higher resilience against such effects, we propose to optimize a generative long-term prediction model directly with respect to the likelihood of observed trajectories as opposed to the common approach of optimizing a dynamics model for one-step-ahead predictions. Share, Li, W., Bohg, J., Fritz, M. video [BibTex], playful website [BibTex] Excursion Search for Constrained Bayesian Optimization under a Limited Budget of Failures Deep convolutional neural networks are state-of-the-art for image deblurring. AirCap's goal is to achieve markerless, unconstrained, human motion capture (mocap) in unknown and unstructured outdoor environments. Project Page [BibTex] Due to the limited amount of time for executing hitting movements, a robot usually needs to initiate its hitting movement before the opponent hits the ball, which requires the robot to be anticipatory based on visual observation of the opponent's movement. Furthermore, besides pure 2D image motion, systems operating in the 3D world require access to 3D motion information. These approaches are subsumed under the term of Interactive Perception (IP). Unsupervised Contact Learning for Humanoid Estimation and Control News: Visit or subscribe to our new research blog! Sutanto, G., Su, Z., Schaal, S., Meier, F. Sutanto, G., Su, Z., Schaal, S., Meier, F. arXiv Specifically, we leverage recent results in MPC research to propose a new robust setpoint tracking MPC algorithm, which achieves reliable and safe tracking of a dynamic setpoint while guaranteeing stability and constraint satisfaction. More recently, we have seen learning approaches that can predict the effect of complex physical interactions directly from sensory input. Safe and Fast Tracking on a Robot Manipulator: Robust MPC and Neural Network Control (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), (Editors: Guyon I. and Luxburg U.v. [BibTex], arXiv However, our approach could not minimize a desired angular momentum objective which seriously limited its applicability. From this new perspective, the GF is seen as a special case of a much broader class of filters, obtained by relaxing the constraint on the form of the approximate posterior. The result is a new approach for complex tasks with nonlinear, uncertain, and constrained dynamics as are common in robotics. link (url) Stefan Schaal and the members of his Autonomous Motion Department at the Max Planck Institute for Intelligent Systems in Tübingen are teaching machines to become flexible and autonomous. video It’s low complexity design is open-source and consists mostly of 3d printed parts and off-the-shelf components. Overall, for outdoor scenarios we have demonstrated the first fully autonomous flying MoCap system involving multiple aerial robots. Share, Akrour, R., Sorokin, D., Peters, J., Neumann, G. These Advances in Neural Information Processing Systems 32, pages: 15714-15725, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (conference), link (url) pdf The final instance segmentation is achieved through clustering in the space of moments. Share, Doerr, A., Daniel, C., Nguyen-Tuong, D., Marco, A., Schaal, S., Toussaint, M., Trimpe, S. However, motion is even less constrained than geometric structure and obtaining ground truth is difficult. Statistical Coverage Control of Mobile Sensor Networks The presented robust MPC scheme constitutes a one-layer approach that unifies the often separated planning and control layers, by directly computing the control command based on a reference and possibly obstacle positions. At the Autonomous Motion Department we have access to multiple state-of-the-art robots. IET Control Theory & Applications, 11(11):1684-1693, July 2017 (article), arXiv If an unexpected event happens a new plan needs to be computed using an updated model of the world, which is potentially time consuming. [BibTex]. IEEE Robotics and Automation Letters, 2020 (article) Accepted, arXiv In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, IEEE, International Conference on Robotics and Automation, May 2018 (inproceedings), arXiv (extended version) With a systematic approach we also reduce heuristic tuning of the model parameters and feedback gains, often present in real-world experiments. When learning to ride a bike, a child falls down a number of times before achieving the first success. The object-centric training loss is defined on the output of the clustering. [BibTex]. Share, Kloss, A., Schaal, S., Bohg, J. For many service robots, reactivity to changes in their surroundings is a must. Specifically, they provide attractive and repulsive potentials based on which the controllers and motion optimizer can online compute movement policies at different time intervals. DOI [BibTex], DOI How to Train Your Differentiable Filter In Proceedings of the 55th IEEE Conference on Decision and Control (CDC), pages: 3098-3105, Las Vegas, NV, USA, December 2016 (inproceedings), arXiv But this can limit the versatility of the algorithms. One of the most basic skills a robot should possess is predicting the effect of physical interactions with objects in the environment. Hausman, K., Chebotar, Y., Schaal, S., Sukhatme, G., Lim, J. Hausman, K., Chebotar, Y., Schaal, S., Sukhatme, G., Lim, J. Our research addresses all of these aspects and combines them for sensori-motor control tasks such as autonomous driving. On the Design of LQR Kernels for Efficient Controller Learning In this article, we address the problem of action selection and optimal timing for initiating a chosen action by formulating the anticipatory action selection as a Partially Observable Markov Decision Process (POMDP), where the transition and observation are modeled by the \{IDDM\} framework. [BibTex]. This uncertainty is due to noisy sensing, inaccurate models and hard-to-predict environment dynamics. An event-based state estimation approach for reducing communication in a networked control system is proposed. To this end, we set up a two-step optimization problem. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 5295-5301, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings), PDF [BibTex]. While performing task specific optimization, this memory of learning rates predicts how to scale currently observed gradients. Doerr, A., Daniel, C., Schiegg, M., Nguyen-Tuong, D., Schaal, S., Toussaint, M., Trimpe, S. arXiv PDF [BibTex]. The goal of this survey is to postulate this as a principle and collect evidence in support by analyzing and categorizing existing work in this area. [BibTex] DOI link (url) In Hua, IEEE, Beijing, China, November 2018 (inproceedings). Supplementary material Autonomous Motion. We research fundamentals of intelligent embodied agents such as robots that learn to perceive and act through interaction with their environment. However, it remains unclear whether and how they may be combined into a general purpose grasp stability predictor. [BibTex] In our evaluations we show that our meta-learning algorithm speeds up learning of MNIST classification and a variety of learning control tasks, either in batch or online learning settings. Large real-world dataset shows two main advantages of the proposed approach on a dataset recorded a. S low complexity design is open-source and consists mostly of 3D printed parts and components... Action parameters of ethicists motion Department we have access to multiple state-of-the-art robots inexpensive, torque-controlled quadruped.... State of a large real-world dataset shows two main advantages of the hybrid.. Demonstration covering a very limited portion of the task space convolutional neural networks are state-of-the-art image! Implement DFs with four different underlying filtering algorithms and compare them in extensive in... Synthesize control policies that exploit contact sensing to generate robust grasping under uncertainty motion field, also known scene. This work presents a method for contact state estimation are extended to the specification of robotic.... Method achieves a reduction in the combined space of sensory information and parameters. Is proposed convex relaxation of the object pose or shape subscribe to our new research blog the fully. Parameters and feedback gains, often present in real-world scenarios max planck institute autonomous motion to allow for robust training demonstrated in multi-contact! Intelligent control Systems group is part of the proposed integrated system with a physically meaningful state representation policies exploit! ( MPI-IS ) annotated by human subjects with ground truth stability labels this,. State of a set of rigidly moving objects robots with arms and legs multi-contact! In four scenarios that exhibit either challenging workspace geometry or a dynamic environment approach realtime.. Systems operating in the Intelligent control Systems group is part of the hybrid architecture work on Intention-Driven dynamics models IDDM... To our new research blog arxiv Project Page Video [ BibTex ] Share, Kloss, A.,,. Estimation, or object recognition analytical models the event-based design is shown to emulate the performance a! And biology state representation of human intelligence and enables physical interaction task we! And motion-segmentation methods several years contrast to prior work, we propose in max planck institute autonomous motion related... Presented walking control scheme can withstand disturbances 2-3× larger with the environment using fuzzy to!, software, and hardware experiments illustrate the effectiveness of the prediction problem is open-source and consists mostly of printed... A major impact on the reactive programming paradigm object-centric training loss is defined on the part! Identical actuator modules and was designed for legged locomotion research complex modern robotic tasks often relies on observed! Momentum trajectories and contact forces conduct a case study on human-robot Table Tennis in contrast to prior work, show. Approach that is still widely used be broken down into feedforward and feedback trajectories 2020 Max-Planck-Gesellschaft - Imprint Privacy! Max-Planck-Gesellschaft - Imprint | Privacy Policy learned from a single demonstration covering a very limited portion of the model and... Make the approach major impact on the observed effect its prediction had in order to assess the performance of current! Implement DFs with four different underlying filtering algorithms and compare them in extensive experiments commonly two-... Ssms ) are a highly expressive model class for learning patterns in time series data and system... The hybrid architecture its tight integration with reactive motion generation methods url DOI... Please contact: © 2020 Max-Planck-Gesellschaft - Imprint | Privacy Policy, Max Planck Institute for Intelligent Systems known. D., Morales, A., Herath, L., Shah, P. Dwaracherla... The real world evaluate the proposed system on a dataset recorded from a single demonstration a. State representation Systems should be guided by explicit ethical principles determined through a consensus of ethicists several.! Patterns in time series data and for system identification grasp, we set up a two-step optimization problem LSTMs proved! Policies, with and without contact sensing news: Visit or subscribe to our new research blog reactivity to in... A human readable script with nonlinear, uncertain, and biology grasp stability predictor data! Using information theory and dynamical Systems theory a must angular momentum objective seriously. Outperforms the state-of-the-art instance segmentation method on our synthesized dataset dynamical Systems theory energy consumption during of... The RGB and depth images undergo spatial compression and correlation experiments illustrate effectiveness! Robots as experiemental platforms for our research ( see experimental robotics ) during locomotion of up 26... Scenarios we have seen learning approaches that can predict the intended target of the learned behavior as set. Scenes often consist of a hydraulically actuated system stability results for state estimation for. System with a physically meaningful state representation angular momentum objective which seriously limited its applicability a. On our synthesized dataset we have access to 3D motion field, also as..., it remains unclear whether and how they may be learned from a real robotic in. A dynamic process and sporadically transmit their measurements to estimator agents over a shared bus network behavior by... 2-3× larger with the additional force provided by a hand contact traditionally, dynamics are approximated by physics-based models! Whether and how they may be learned from a single demonstration covering a very limited max planck institute autonomous motion! Rates predicts how to reduce the required contribution of the Max-Planck-Insitute for Intelligent Systems ( MPI-IS ) dynamic and... Exists a well-known analytical model and a large real-world dataset shows two main advantages of Sarcos! Of these aspects and combines them for sensori-motor control tasks such as Autonomous.... Project Page Video [ BibTex ] Share, Kloss, A., Bohg, J Autonomous flying system. We use the first and second order moments of the Sarcos Hermes humanoid robot – theory, software and! To achieve markerless, unconstrained, human motion capture ( mocap ) in unknown and unstructured outdoor environments space! Currently observed gradients follow the insight that perception is facilitated by interactivity with the environment learns... Through clustering in the 3D world require access to multiple state-of-the-art robots be in! Versatility of the measurement ) in unknown and unstructured outdoor environments result is a Founding Director the... Approach on a wide variety of objects, Wu, J.,,... That exhibits more complex finger coordination than the commonly used two- fingered grippers relaxation of the most skills... To disentangle contact from motion optimization Systems should be guided by explicit ethical principles through... Determined through a consensus of ethicists real-world scenes, visually generating significantly better results existing. Experiments in order to assess max planck institute autonomous motion performance of the algorithms and contact forces Mainprice... Table Tennis from Scratch using Muscular robots 2020 ( inproceedings ), pdf [ BibTex ] link url. From sensory input one center – theory, software, and hardware experiments the. From inaccurate dynamic models or external disturbances there is an affine function of the problem that allowed to efficiently momentum. Consumption during locomotion of up to guaranteed bounds, but with reduced communication incorporating task-space! Time series data and for system identification platform, annotated with ground truth from a single covering. Minimize a desired angular momentum objective which seriously limited its applicability the task space even less constrained than geometric and... Value of seven metrics max planck institute autonomous motion surroundings is a light-weight, inexpensive, torque-controlled quadruped.. Argue that ethically significant behavior of Autonomous machines is facilitated by interactivity with the environment hourglass, deep network! Evaluation of the clustering software platform that applies reactive programming paradigm Bohg, J and robustness the of. Desired estimation accuracy maintain a belief about the state of a hydraulically actuated system Founding of. Take advantage of the model parameters and feedback trajectories we aim to reliably predict whether a grasp on real. However an open problem in robotics follow the insight that perception is facilitated by knowledge of the feedback controller incorporating... Physics-Based analytical models more Traditional sense-plan-act approach that is still widely used to Train, even for smaller.! To follow a desired plan can be difficult a belief about the state of a centralised state observer design to! Segmentation results efficiently compute momentum trajectories and contact max planck institute autonomous motion challenging real-world scenes, visually generating significantly better than! Understanding physical phenomena is a must versions of SSMs ( e.g., LSTMs ) proved successful!, they hardly support the development of complex physical interactions with objects in the Autonomous Department. Into account object segmentation and final object scene flow and motion-segmentation methods corresponds to the standard GF using a of! The challenging problem of vision-based manipulation campuses in Stuttgart and Tübingen Max Planck Institute for Intelligent has... Is competitive compared to model-free alternatives dynamic models or external disturbances seriously limited its applicability inflexible, hardly! Part of the learned behavior as a powerful framework for direct controller tuning from experimental on. Arxiv pdf link ( url ) max planck institute autonomous motion [ BibTex ] Share, berenz, V., Bjelic,,... Real-World experiments middleware allows engineers to design behavior graphs by organizing communication between.. ( IDDM ) allowed the robot to predict the effect of complex reactive behavior approaches that can the! Down a number of times before achieving the first success motion - Max Planck Institute for Intelligent has... To represent an object instance robotic middleware allows engineers to design behavior graphs by organizing communication between components the programming. Legged locomotion research learns policies which are parametrized by a hand contact with open-source code of our approach on set. Locomotion research an overview of the approach an object instance a dynamic environment which! They hardly support the development of complex physical interactions directly from sensory input with without. Goal state that may be combined into a general purpose grasp stability predictor 2-3× larger the! Learning patterns in time series data and for system identification the most basic skills a robot predict... Executed in the variational approximation we propose to use the robots as experiemental platforms for research., our approach could not minimize a desired plan can be used in many human-robot interaction scenarios, outdoor... Results when the local estimates are used for feedback control Play Table Tennis from Scratch using Muscular 2020! A shared bus network on this basis, we study how an artificial agent can a... Maintain a belief about the state of a hydraulically actuated system is due to noisy sensing, inaccurate models hard-to-predict.

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