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Item type:Publication, Access status: without files , An integrated approach to navigation and control in micro underwater robotics using radio-frequency localizationNavigation and control are a largely unsolved problems for micro autonomous underwater vehicles (). The main challenges are due to the lack of accurate underwater localization systems, which fit on-board of . In this work, we present an integrated navigation and control architecture consisting of a low-cost embedded localization module and an underwater way-point tracking controller, which fulfills the requirements of . The performance of the navigation and control system is benchmarked in two different experimental scenarios.Publicationtype: Conference Paper211 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Residual reinforcement learning for robot controlConventional feedback control methods can solve various types of robot control problems very efficiently by capturing the structure with explicit models, such as rigid body equations of motion. However, many control problems in modern manufacturing deal with contacts and friction, which are difficult to capture with first-order physical modeling. Hence, applying control design methodologies to these kinds of problems often results in brittle and inaccurate controllers, which have to be manually tuned for deployment. Reinforcement learning (RL) methods have been demonstrated to be capable of learning continuous robot controllers from interactions with the environment, even for problems that include friction and contacts. In this paper, we study how we can solve difficult control problems in the real world by decomposing them into a part that is solved efficiently by conventional feedback control methods, and the residual which is solved with RL. The final control policy is a superposition of both control signals. We demonstrate our approach by training an agent to successfully perform a real-world block assembly task involving contacts and unstable objects.Publicationtype: Conference Paper145 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Micro underwater vehicle hydrobatics: a submerged furuta pendulum(IEEE, 2018-09); ; ; ; We present the new HippoCampus micro underwater vehicle, first introduced in [1]. It is designed for monitoring confined fluid volumes. These tightly constrained settings demand agile vehicle dynamics. Moreover, we adapt a robust attitude control scheme for aerial drones to the underwater domain. We demonstrate the performance of the controller with a challenging maneuver. A submerged Furuta pendulum is stabilized by HippoCampus after a swing-up. The experimental results reveal the robustness of the control method, as the system quickly recovers from strong physical disturbances, which are applied to the system.Publicationtype: Conference Paper329 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Sealing of machine parts and modules manufactured with desktop 3D printersThe 3D printing technology is taking over development departments all over the world because it enables a fast and flexible production of prototypes. Such as with any other manufacturing process, "best practices" exist for generative manufacturing as well. While design guidelines for 3D printing provide general recommendations, guidelines which specifically deal with sealing of printed components and modules are missing so far. Factors such as water pressure or material properties themselves influence negatively the sealing capabilities of a system consisting of 3D printed parts. This paper analyzes key aspects for designing 3D printed parts, when sealing is important. The presented methods are applied to the design of a micro autonomous underwater vehicle.Publicationtype: Journal Article166