Multi-Step Prediction of Occupancy Grid Maps with Recurrent Neural Networks

no code implementations • CVPR 2019 • Nima Mohajerin, Mohsen Rohani

Although in the transformed sequences the KITTI dataset is heavily biased toward static objects, by learning the difference between subsequent OGMs, our proposed method provides accurate prediction over both the static and moving objects.

Autonomous Driving Prediction Of Occupancy Grid Maps

Multi-Step Prediction of Dynamic Systems with Recurrent Neural Networks

no code implementations • 20 May 2018 • Nima Mohajerin, Steven L. Waslander

In this work, the state initialization problem is addressed using Neural Networks (NNs) to effectively train a variety of RNNs for modeling two aerial vehicles, a helicopter and a quadrotor, from experimental data.