C
Christian Frey
Researcher at Fraunhofer Society
Publications - 22
Citations - 286
Christian Frey is an academic researcher from Fraunhofer Society. The author has contributed to research in topics: Robot & Mobile robot. The author has an hindex of 9, co-authored 22 publications receiving 240 citations.
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Proceedings ArticleDOI
SENEKA - sensor network with mobile robots for disaster management
Helge-Björn Kuntze,Christian Frey,Igor Tchouchenkov,Barbara Staehle,Erich Rome,Kai Pfeiffer,Andreas Wenzel,Jürgen Wöllenstein +7 more
TL;DR: The aim of this paper is to inform on the goals and first research results of the ongoing joint research project SENEKA, which targets the integration of the robot-sensor network into the operation procedures of the rescue teams.
Proceedings Article
Application of Hybrid A* to an Autonomous Mobile Robot for Path Planning in Unstructured Outdoor Environments
TL;DR: This paper presents the application of the Hybrid A* algorithm to a nonholonomic mobile outdoor robot in order to plan near optimal paths in mostly unknown and potentially intricate environments.
Proceedings ArticleDOI
Deep-sea AUV navigation using side-scan sonar images and SLAM
Philipp Woock,Christian Frey +1 more
TL;DR: An overview of existing approaches to underwater SLAM using sonar data is given and a short outlook to the system that will be used in the TIETeK project is presented.
Proceedings ArticleDOI
Monitoring of complex industrial processes based on self-organizing maps and watershed transformations
TL;DR: In this article, a monitoring concept based on machine learning methods has been developed, which allows an integrated and continuous diagnosis of the physical process behavior and phases, and presents an approach for the identification of intrinsic process-phases and the monitoring functionality of the unknown process behaviour based on self-organizing-maps and watershed transformations.
Proceedings ArticleDOI
Safe mobile robot motion planning for waypoint sequences in a dynamic environment
TL;DR: A novel graph structure based on a state × time × goal lattice with hybrid dimensionality which allows the joint planning for multiple goals while incorporating collision risk due to dynamic and static obstacles and computes hybrid solutions which are part trajectory and part path.