Sebastian Blumenthal

A scene graph based shared 3D world model for robotic applications

This paper presents a novel approach for representing and maintaining a shared 3D world model for robotic applications. This approach is based on the scene graph concept which has been adapted to the requirements of the robotic domain. A key feature is the temporal and centralized sharing of all available 3D data in the leaves of the graph structure. The approach enables tracking of dynamic objects, incorporates uncertainty and allows for annotations by semantic tags. A demonstration is given for a perception application that exploits the temporal sharing of 3D data. A Region of Interest (ROI) is extracted from the stored scene data in order to accelerate processing cycle times.

An approach for a distributed world model with QoS-based perception algorithm adaptation

This paper presents a distributed world model that is able to adapt to changes in the Quality of Service (QoS) of the communication layer by online reconfiguration of perception algorithms. The approach consists of (a) a mechanism for storage, exchange and processing of world model data and (b) a feedback loop that incorporates reasoning techniques to adapt to QoS changes immediately. The latter introduces a Level of Detail (LoD) metric based on a spatial resolution in order to infer an upper bound for the amount of data that can be transmitted without violating an application specific transmission delay. Experiments have been performed with Octree-based subsampling techniques applied to data originating from a RGB-D camera using simulated and real-world data sets for timevarying bandwidth values as employed QoS measure.

Towards identification of best practice algorithms in 3D perception and modeling

Robots need a representation of their environment to reason about and to interact with it. Different 3D perception and modeling approaches exist to create such a representation, but they are not yet easily comparable. This work tries to identify best practice algorithms in the domain of 3D perception and modeling with a focus on environment reconstruction for robotic applications. The goal is to have a collection of refactored algorithms that are easily measurable and comparable. The realization follows a methodology consisting of five steps. After a survey of relevant algorithms and libraries, common representations for the core data-types Cartesian point, Cartesian point cloud and triangle mesh are identified for use in harmonized interfaces. Atomic algorithms are encapsulated into four software components: the Octree component, the Iterative Closest Point component, the k-Nearest Neighbors search component and the Delaunay triangulation component. A sample experiment demonstrates how the component structure can be used to deduce best practice.