Matthias Nieuwenhuisen

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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)
— 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 anthropo-morphic 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(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)
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)
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)
In this paper we describe details of our winning team Nimb-Ro@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 face-to-face communication between(More)
For situations, where mapping is neither possible from high altitudes nor from the ground, we are developing an autonomous micro aerial vehicle able to fly at low altitudes in close vicinity of obstacles. This vehicle is based on a MikroKopter TM octocopter platform (maximum total weight: 5kg), and contains a dual frequency GPS board, an IMU, a compass, two(More)
Perception of the environment is crucial in terms of successfully playing soccer. Especially the detection of other players improves game play skills, such as obstacle avoidance and path planning. Such information can help refine reactive behavioral strategies, and is conducive to team play capabilities. Robot detection in the RoboCup Standard Platform(More)
Reliable obstacle avoidance is a key to navigating with UAVs in the close vicinity of static and dynamic obstacles. Wheel-based mobile robots are often equipped with 2D or 3D laser range finders that cover the 2D workspace sufficiently accurate and at a high rate. Micro UAV platforms operate in a 3D environment, but the restricted payload prohibits the use(More)
— In the last decades, tremendous progress has been made in the field of autonomous indoor navigation for mobile robots. However, these approaches assume the structural part of the environment to be completely static. In practice, movable parts of scenes, e.g. doors, frequently violate this assumption which leads to poor performance. Also, mobile(More)