Christian A. Mueller

WasteAnt GmbH

As digitization advances, stationary retail is increasingly enabled to develop novel retail services aiming at enhancing efficiency of business processes ranging from in-store logistics to customer shopping experiences. In contrast to online stores, stationary retail digitization demands for an integration of various data like location information,...

Conceptual knowledge about objects is essential for humans, as well as for animals, to interact with their environment. On this basis, the objects can be understood as tools, a selection process can be implemented and their usage can be planned in order to achieve a specific goal. The conceptual knowledge, in this case, is primarily concerned about...

Object shape is a key cue that contributes to the semantic understanding of objects. In this work we focus on the categorization of real-world object point clouds to particular shape types. Therein surface description and representation of object shape structure have significant influence on shape categorization accuracy, when dealing with real-wor...

Continuous System Integration and Validation is an increasingly important factor for an efficient system development process. In particular, for underwater projects involving semi- to fully-autonomous robotic systems since they progressively become more complex, need to perform under more challenging environmental conditions and execute more intric...

Tool-use applications in robotics require conceptual knowledge about objects for informed decision making and object interactions. State-of-the-art methods employ hand-crafted symbolic knowledge which is defined from a human perspective and grounded into sensory data afterwards. However, due to different sensing and acting capabilities of robots, t...

Underwater robot interventions require a high level of safety and reliability. A major challenge to address is a robust and accurate acquisition of localization estimates, as it is a prerequisite to enable more complex tasks, e.g. floating manipulation and mapping. State-of-the-art navigation in commercial operations, such as oil & gas production (...

In recent years, the number of maritime exploration and exploitation activities has rapidly increased, and with it the necessity to perform more complex tasks underwater, e.g., floating manipulation and mapping with Remote Operated Vehicles (ROVs). The first step to perform these activities in a reliable manner, is to obtain an accurate robot local...

Intervention missions, that is, underwater manipulation tasks, for example, in the context of oil-&-gas production, require a high amount of precise, robust navigation. In this article, we describe the use of an advanced vision system suited for deep-sea operations, which in combination with artificial markers on target structures like oil-&-gas pr...

An unsupervised shape analysis is proposed to learn concepts reflecting shape commonalities. Our approach is two-fold: i) a spatial topology analysis of point cloud segment constellations within objects is used in which constellations are decomposed and described in a hierarchical and symbolic manner. ii) A topology analysis of the description spac...

We propose a robust gesture-based communication pipeline for divers to instruct an Autonomous Underwater Vehicle (AUV) to assist them in performing high-risk tasks and helping in case of emergency. A gesture communication language (CADDIAN) is developed, based on consolidated and standardized diver gestures, including an alphabet, syntax and semant...

Underwater manipulation is a challenging problem. The state-of-the-art technology is dominated by remotely operated vehicles (ROVs). ROV operations typically require an offshore crew consisting of, at minimum, an intendant (or supervisor), an operator, and a navigator. This crew must often be doubled or even tripled due to work shifts. In addition,...

Robots require knowledge about objects in order to efficiently perform various household tasks involving objects. The existing knowledge bases for robots acquire symbolic knowledge about objects from manually-coded external common sense knowledge bases such as ConceptNet, Word-Net etc. The problem with such approaches is the discrepancy between hum...

We propose a robust gesture-based communication pipeline for divers to instruct an Autonomous Underwater Vehicle (AUV) to assist them in performing high-risk tasks and helping in case of emergency. A gesture communication language (CADDIAN) is developed, based on consolidated and standardized diver gestures, including an alphabet, syntax and semant...

Deep-sea robot operations demand a high level of safety, efficiency and reliability. As a consequence, measures within the development stage have to be implemented to extensively evaluate and benchmark system components ranging from data acquisition, perception and localization to control. We present an approach based on high-fidelity simulation th...

When a robot is operating in a dynamic environment, it can- not be assumed that a tool required to solve a given task will always be available. In case of a missing tool, an ideal re- sponse would be to find a substitute to complete the task. In this paper, we present a proof of concept of a grounded knowledge-based approach to tool substitution. I...

A topological shape analysis is proposed and utilized to learn concepts that reflect shape commonalities. Our approach is two-fold: i) a spatial topology analysis of point cloud segment constellations within objects. Therein constellations are decomposed and described in an hierarchical manner – from single segments to segment groups until a single...

Robots require knowledge about objects in order to efficiently perform various household tasks involving objects. The existing knowledge bases for robots acquire symbolic knowledge about objects from manually-coded external common sense knowledge bases such as ConceptNet, WordNet etc. The problem with such approaches is the discrepancy between huma...

When a robot is operating in a dynamic environment, it cannot be assumed that a tool required to solve a given task will always be available. In case of a missing tool, an ideal response would be to find a substitute to complete the task. In this paper, we present a proof of concept of a grounded knowledge-based approach to tool substitution. In or...

Deep-sea robotic operations require a high level of safety, efficiency and reliability. In the development stage of such systems, measures have to be taken into account to validate performance in order to assess the achievement of these requirements. In the context of continuous system integration, we proposed a simulation-in-the-loop framework foc...

Object shape is a key cue that contributes to the semantic understanding of objects. In this work we focus on the categorization of real-world object point clouds to particular shape types. Therein surface description and representation of object shape structure have significant influence on shape categorization accuracy, when dealing with real-wor...

A topological shape analysis is proposed and utilized to learn concepts that reflect shape commonalities. Our approach is two-fold: i) a spatial topology analysis of point cloud segment constellations within objects. Therein constellations are decomposed and described in an hierarchical manner - from single segments to segment groups until a single...

Scenario: A rescue team needs to cross a partially damaged bridge in a flooded area. It is unknown whether the construction is still able to carry a vehicle. Assessing the construction's integrity can be accomplished by the analysis of the bridge's eigenfrequencies. Rather than using proprietary expensive Vibration Measurement Systems (VMS) we prop...

ROV operations are expensive and there is an urge to improve on their efficiency and speed. The EU project " Effective Dexterous ROV Operations in Presence of Communications Latencies (DexROV) " proposes a solution to those needs by developing a set of hardware and software tools to support the teleoperation of ROVs over a satellite link, i.e., fro...

Within the EU FP7 project " Cognitive autonomous diving buddy (CADDY) " , work has been made to assist and monitor divers through Autonomous Underwater Vehicles (AUVs) during their long underwater expeditions. To achieve this goal, one milestone is to give the AUV the capability to track the diver's whereabouts at all times. Inertial sensors are mo...

Deep-sea operations of remotely-operated vehicles (ROV) need robust testing and deployment strategies beyond the traditional pre-deployment validation on real hardware. Seamless integration of simulated components into the validation pipeline allows for rapid development of components and validation under controlled conditions. We describe the bene...

Bridges are fragile transport infrastructure elements which require special attention in evacuation planning within flood disaster scenarios. In this paper we present work on a bridge inspection procedure with a marine vehicle in which a bridge statics analysis expert assesses the condition of the bridge from a safe operating station. Given bridge...

The operation of a ROV requires significant off-shore dedicated manpower to handle and operate the robotic platform. In order to reduce the burden of operations, DexROV proposes to work out more cost effective and time efficient ROV operations, where manned support is in a large extent delocalized onshore (i.e. from a ROV control center), possibly...

We present a framework to generate watertight mesh representations in an unsupervised manner from noisy point clouds of complex, heterogeneous objects with free-form surfaces. The resulting meshes are ready to use in applications like kinematics and dynamics simulation where watertightness and fast processing are the main quality criteria. This wor...

This article discusses the scientifically and industrially important problem of automating the process of unloading goods from standard shipping containers. We outline some of the challenges barring further adoption of robotic solutions to this problem: ranging from handling a vast variety of shapes, sizes, weights, appearance and packing arrangeme...

Autonomous robots in unstructured and dynamically changing retail environments have to master complex perception, knowledgeprocessing, and manipulation tasks. To enable them to act competently, we propose a framework based on three core components: (o) a knowledge-enabled perception system, capable of combining diverse information sources to cope w...

Autonomous robots in unstructured and dynamically changing retail environments have to master complex perception, knowledge processing, and manipulation tasks. To enable them to act competently, we propose a framework based on three core components: (o) a knowledge-enabled perception system, capable of combining diverse information sources to cope...

We present a framework to generate watertight mesh representations in an unsupervised manner from noisy point clouds of complex, heterogeneous objects with free-form surfaces. The resulting meshes are ready to use in applications like kinematics and dynamics simulation where watertightness and fast processing are the main quality criteria. This wor...

We present an approach for object class learning using a part-based shape categorization in RGB-augmented 3D point clouds captured from cluttered indoor scenes with a Kinect-like sensor. We propose an unsupervised hierarchical learning procedure which allows to symbolically classify shape parts by different specificity levels of detailedness of the...

The work presented here is embedded in research on an industrial application scenario, namely autonomous shipping-container unloading, which has several challenging constraints: the scene is very cluttered, objects can be much larger than in common table-top scenarios; the perception must be highly robust, while being as fast as possible. These con...

We present an approach for object class learning using a part-based shape categorization in RGB-augmented 3D point clouds captured from cluttered indoor scenes with a Kinect-like sensor. A graph representation is used to detect and categorize object instances based on part-constellations found in scenes. No assumptions like objects being placed on...

Surface reconstruction is a crucial step to convert unstructured point clouds to a compact representation. In this paper we introduce a modified Growing Neural Gas (GNG) algorithm for surface reconstruction of free-formed objects found in domestic environments. In our experiments we show that the algorithm generates consistent surfaces and is able...

An efficient object perception is a crucial component of a mobile service robot. In this work we present a solution for visual categorization of objects. We developed a prototypic categorization system which classifies unknown objects based on their visual properties to a corresponding category of predefined domestic object categories. The system u...

In this article we describe the architecture, algorithms and real-world benchmarks performed by Johnny Jackanapes, an autonomous service robot for domestic environments. Johnny serves as a research and development platform to explore, develop and integrate capabilities required for real-world domestic service applications. We present a control arch...

An efficient object perception is a crucial component of a mobile service robot. In this work we present a solution for visual cate-gorization of objects. We developed a prototypic categorization system which classifies unknown objects based on their visual properties to a corresponding category of predefined domestic object categories. The system...