Footnote:
Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
Description:
A key challenge in robotic systems is how to interpret all the data coming from the sensors on-board the system, and how to select the right environment representation that is beneficial for the task at hand. These challenges are particularly difficult for robots that operate in cluttered environments since objects are ambiguous and tough to distinguish in clutter. Moreover, if a robot needs to physically interact with objects, its internal representation needs to be informative enough to perform the intended interaction, and flexible enough to handle the consequences of its actions. One common application that captures these challenges is object finding in clutter, which in addition to passive visual inspection, often requires interaction to reveal the hidden parts of the environment. To interact, robots need to have some knowledge about the target object, e.g. an object model, and need an environment representation that, together with proprioceptive sensing, contains sufficient information to complete a task successfully. This thesis aims to develop an interactive perception framework for robots. Towards this aim the focus is on (i) how to generate and update object models and (ii) how to develop a flexible planning framework for object interaction. The first part of this thesis presents a dataset of household objects and box scenes containing those objects (CLUBS), commonly found in warehouses. The process of data collection with multiple RGB-D cameras mounted on a robotic arm, and accurate object model generation is described. An image annotation pipeline, and object 3D bounding box estimation approach is also proposed. The box scenes within the dataset contain up to 40 household objects in different configurations, and with different levels of clutter. The variability of the provided data is beneficial for evaluating tasks such as object detection, segmentation, reconstruction, and object completion. Since these scenes also contain 2D object bounding boxes and per frame pixel-wise labels, and 3D object ...