Speaker
Description
Abstract— Space robotics covers a wide field of applications. It ranges form exploration tasks (robotic vehicle with measuring equipment [1]) to servicing or maintenance tasks (on-orbit servicing or deorbiting of satellites [2], [3]). These tasks comprise different grades of autonomy from telepresence scenarios [4] to semi autonomous supporting task [3] to completely autonomous applications. Depending on this also the system complexity of the robot varies from small modules developed for a dedicated task [5] to highly complex versatile robotic systems (e.g. a rover for exploration [1] or a humanoid robot which performs tasks on a planetary surface in supervised autonomy scenario [6]). However all robotic systems follow regarding data processing an equal approach: a control model processes actual data sets acquired from sensors to data sets for actuators to obtain the desired reaction of the robot. Depending on the task and the robotic system the involved data processing have to be performed from a single processor up to a distributed system. Especially highly complex robotic system with cascaded control loops spatially distributed over arbitrary processing units demand for strict realtime requirements regarding synchronization and main control loop frequency [7]. These requirements together with the introduction of big data and machine learning approaches into the robotic domain issues a big challenge to on-board data processing.
| Paper submission | Yes |
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