The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, a robot learning approach is proposed which integrates Visuospatial Skill Learning, Imitation Learning, and conventional planning methods. In our approach, the sensorimotor skills (i.e., actions) are learned through a learning from demonstration strategy. The sequence of performed actions is learned through demonstrations using Visuospatial Skill Learning. A standard action-level planner...
This paper investigates learning approaches for discovering fault-tolerant control policies to overcome thruster failures in Autonomous Underwater Vehicles (AUV). The proposed approach is a model-based direct policy search that learns on an on-board simulated model of the vehicle. When a fault is detected and isolated the model of the AUV is reconfigured according to the new condition. To discover...
A learning approach is proposed for the challenging task of autonomous robotic valve turning in the presence of active disturbances and uncertainties. The valve turning task comprises two phases: reaching and turning. For the reaching phase the manipulator learns how to generate trajectories to reach or retract from the target. The learning is based on a set of trajectories demonstrated in advance...
We investigate methods to improve fault-tolerance of Autonomous Underwater Vehicles (AUVs) to increase their reliability and persistent autonomy. We propose a learning-based approach that is able to discover new control policies to overcome thruster failures as they happen. The proposed approach is a model-based direct policy search that learns on an on-board simulated model of the AUV. The model...
In this paper we propose covariance analysis as a metric for reinforcement learning to improve the robustness of a learned policy. The local optima found during the exploration are analyzed in terms of the total cumulative reward and the local behavior of the system in the neighborhood of the optima. The analysis is performed in the solution space to select a policy that exhibits robustness in uncertain...
This paper proposes a novel interactive robot learning approach for acquiring visuospatial skills. It allows a robot to acquire new capabilities by observing a demonstration while interacting with a human caregiver. Most existing learning from demonstration approaches focus on the trajectories, whereas in our approach the focus is placed on achieving a desired goal configuration of objects relative...
We present a novel robot learning approach based on visual perception that allows a robot to acquire new skills by observing a demonstration from a tutor. Unlike most existing learning from demonstration approaches, where the focus is placed on the trajectories, in our approach the focus is on achieving a desired goal configuration of objects relative to one another. Our approach is based on visual...
Autonomous valve turning is an extremely challenging task for an Autonomous Underwater Vehicle (AUV). To resolve this challenge, this paper proposes a set of different computational techniques integrated in a three-layer hierarchical scheme. Each layer realizes specific subtasks to improve the persistent autonomy of the system. In the first layer, the robot acquires the motor skills of approaching...
We propose a method for computing on-line the controller of an Autonomous Underwater Vehicle under thruster failures. The method is general and can be applied to both redundant and under-actuated AUVs, as it does not rely on the modification of the thruster control matrix. We define an optimization problem on a specific class of functions, in order to compute the optimal control law that achieves...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.