Team NimbRo Logistics is based in the Autonomous Intelligent Systems Group at the Computer Science Institute of University of Bonn, Germany.
The University of Bonn is one of the leading public research universities of Germany. Its Computer Science Institute has a long tradition in robotics research, especially in the areas of mobile robotics and SLAM. Since 2008, the Autonomous Intelligent Systems (AIS) group conducts research in cognitive robotics and machine learning.
The AIS group has extensive experience in real-time perception, control, and system integration for complex robots, including cognitive service robots capable of mobile manipulation and intuitive human-robot interaction in complex environments. We developed leading RGB-D SLAM, semantic mapping, and planning methods for navigation and manipulation.
The AIS group has extensive experience in robot competitions and challenges. Our team NimbRo participates with great success at the international RoboCup competitions, winning a total of 13 tournaments, including the last five years of the Humanoid TeenSize soccer league and the last three years of the @Home domestic service robot league. Recently, we developed also a robot for mobile manipulation in rough terrain, which participated at the DLR SpaceBot Cup.
Our team has the necessary expertise to address the objectives of Challenge 2. We developed the cognitive service robots Dynamaid and Cosero which have an anthropomorphic upper body and an omnidirectional drive. These robots are equipped with multiple laser scanners, an RGB-D camera, a high-resolution camera, a directed microphone, an Intel Core-i7 Quad onboard PC, and a high-performance wireless module. We developed efficient methods for environment mapping, object detection, navigation and manipulation planning. In the RoboCup@Home competitions, the robots demonstrated picking and placing objects, dual-arm manipulation of larger objects, the opening and closing of doors, the use of tools, and many other skills. In the FP7 ECHORD experiment ActReMa, we implemented bin picking for these mobile robots. In the new FP7 project STAMINA, we develop bin picking for the transportable robots UR10 and Baxter.
The team members cover all relevant aspects, from environment mapping and robot localization, over object detection and recognition, to navigation and manipulation planning. Our team has not only the necessary technical expertise, but also plenty of experience with robot competitions and challenges. We also have experience in the cooperation with project partners from industry.
- Approximate Triangulation and Region Growing for Efficient Segmentation and Smoothing of Range Images (PDF)
- Demonstrating Everyday Manipulation Skills in RoboCup@Home (PDF)
- Efficient Deformable Registration of Multi-Resolution Surfel Maps for Object Manipulation Skill Transfer (PDF)
- Increasing Flexibility of Mobile Manipulation and Intuitive Human-Robot Interaction in RoboCup@Home (PDF)
- Dense Real-Time Mapping of Object-Class Semantics from RGB-D Video (PDF)
- Mobile Bin Picking with an Anthropomorphic Service Robot (PDF)
- Efficient 3D object Perception and Grasp Planning for Mobile Manipulation in Domestic Environmnets (PDF)