Name: CS::APEX - The Algorithm Prototyper and EXperimentor is a tool for visual programming and data flow driven design, written in C++. The framework provides a platform for rapid prototyping of cognitive algorithms, like computer vision and point cloud processing. To achieve reusability, functionality is implemented using computation nodes.
Last Release: 2015-03-04
Name: GeRoNa (Generic Robot Navigation) - A modular robot navigation framework, that bundles path planning and path following (including obstacle detection) and manages communication between the individual modules. It is designed to be easily extensible for new tasks and robot models.
Last Release: 2017-05-12
On this page we provide an overview of different datasets for benchmarking and retracing experimental results. Some of the datasets were published along with one of our scientific papers.
Deep Learning Datasets
PeopleOnGrass provides a simply object detection playground dataset to experiment with meta data. Each image is accompanies with precise information about its capture altitude, angle, time and so on.
SeaDronesSee is the first maritime datasets aimed at search and rescue to find people in open water. It consists of an object detection and tracking part.
Multi-Sensor 3D Person Detection Dataset
This page provides a 3D person detection dataset compilation. The compilation contains 3D indoor and outdoor recorded with different sensor types at once.
UHF RFID Dataset for Mapping RFID in 3D
The page provides a dataset used by Ran Liu, Artur Koch and Andreas Zell in Mapping UHF RFID Tags with a Mobile Robot using 3D Sensor Model.
AmbiSense UHF RFID Benchmark Dataset for Location Fingerprinting and Robotic Self-Localization
The page provides details on the experimental setup and downloadable experimental data used by Philipp Vorst, Artur Koch and Andreas Zell in Efficient Self-Adjusting, Similarity-based Location Fingerprinting with Passive UHF RFID. The datasets can serve as benchmarks and experimental data for location fingerprinting using passive UHF RFID.
This page provides the 3D reconstructions, generated with KinFu, of four objects at different distances. The point clouds used to generate the reconstructions were recorded with six different RGBD sensors.