10 citations · 15 across the 4 of their papers we have counts for
5 papers
Self-Supervised Flow Estimation using Geometric Regularization with Applications to Camera Image and Grid Map Sequences
Sascha Wirges, Johannes Gräter, Qiuhao Zhang +1
We present a self-supervised approach to estimate flow in camera image and top-view grid map sequences using fully convolutional neural networks in the domain of automated driving.…
Cooperative Motion Planning for Non-Holonomic Agents with Value Iteration Networks
Eike Rehder, Maximilian Naumann, Niels Ole Salscheider +1
Cooperative motion planning is still a challenging task for robots. Recently, Value Iteration Networks (VINs) were proposed to model motion planning tasks as Neural Networks. In th…
Towards Cooperative Motion Planning for Automated Vehicles in Mixed Traffic
Maximilian Naumann, Christoph Stiller
While motion planning techniques for automated vehicles in a reactive and anticipatory manner are already widely presented, approaches to cooperative motion planning are still rema…
RegNet: Multimodal Sensor Registration Using Deep Neural Networks
Nick Schneider, Florian Piewak, Christoph Stiller +1
In this paper, we present RegNet, the first deep convolutional neural network (CNN) to infer a 6 degrees of freedom (DOF) extrinsic calibration between multimodal sensors, exemplif…
Pedestrian Prediction by Planning using Deep Neural Networks
Eike Rehder, Florian Wirth, Martin Lauer +1
Accurate traffic participant prediction is the prerequisite for collision avoidance of autonomous vehicles. In this work, we predict pedestrians by emulating their own motion plann…