Matthias Nieuwenhuisen

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Grasping individual objects from an unordered pile in a box has been investigated in static scenarios so far. In this paper, we demonstrate bin picking with an anthropomorphic mobile robot. To this end, we extend global navigation techniques by precise local alignment with a transport box. Objects are detected in range images using a shape primitive-based(More)
Micro aerial vehicles, such as multirotors, are particularly well suited for the autonomous monitoring, inspection, and surveillance of buildings, e.g., for maintenance or disaster management. Key prerequisites for the fully autonomous operation of micro aerial vehicles are real-time obstacle detection and planning of collision-free trajectories. In this(More)
Domestic service tasks require three main skills from autonomous robots: robust navigation in indoor environments, flexible object manipulation, and intuitive communication with the users. In this report, we present the communication skills of our anthropomorphic service and communication robots Dynamaid and Robotinho. Both robots are equipped with an(More)
Exploration strategies are an important ingredient for map building with mobile robots. The traditional greedy exploration strategy is not directly applicable in unbounded outdoor environments, because it decides on the robot’s actions solely based on the expected information gain and travel cost. As this value can be optimized by driving straight into(More)
Reliably perceiving obstacles and avoiding collisions is key for the fully autonomous application of micro aerial vehicles (MAVs). Limiting factors for increasing autonomy and complexity of MAVs are limited onboard sensing and limited onboard processing power. In this paper, we propose a complete system with a multimodal sensor setup for omnidirectional(More)
Limiting factors for increasing autonomy and complexity of truly autonomous systems (without external sensing and control) are onboard sensing and onboard processing power. In this paper, we propose a hardware setup and processing pipeline that allows a fully autonomous UAV to perceive obstacles in (almost) all directions in its surroundings. Different(More)
Grasping objects from unstructured piles is an important, but difficult task. We present a new framework to grasp objects composed of shape primitives like cylinders and spheres. For object recognition, we employ efficient shape primitive detection methods in 3D point clouds. Object models composed of such primitives are then found in the detected shapes(More)
In this paper we describe details of our winning team NimbRo@Home at the RoboCup@Home competition 2012. This year we improved the gripper design of our robots and further advanced mobile manipulation capabilities such as object perception and manipulation planning. For human-robot interaction, we propose to complement faceto-face communication between user(More)
Grasping individual objects from an unordered pile in a box has been investigated in stationary scenarios so far. In this work, we present a complete system including active object perception and grasp planning for bin picking with a mobile robot. At the core of our approach is an efficient representation of objects as compounds of simple shape and contour(More)