9 citations · 10 across the 3 of their papers we have counts for
6 papers
Optimal Control of Hybrid Systems via Measure Relaxations
Etienne Buehrle, Ömer Şahin Taş, Christoph Stiller
We propose an approach to trajectory optimization for piecewise polynomial systems based on the recently proposed graphs of convex sets framework. We instantiate the framework with…
RedMotion: Motion Prediction via Redundancy Reduction
Royden Wagner, Omer Sahin Tas, Marvin Klemp +2
We introduce RedMotion, a transformer model for motion prediction in self-driving vehicles that learns environment representations via redundancy reduction. Our first type of redun…
Efficient Sampling in POMDPs with Lipschitz Bandits for Motion Planning in Continuous Spaces
Ömer Şahin Taş, Felix Hauser, Martin Lauer
Decision making under uncertainty can be framed as a partially observable Markov decision process (POMDP). Finding exact solutions of POMDPs is generally computationally intractabl…
Decision-Time Postponing Motion Planning for Combinatorial Uncertain Maneuvering
Ömer Şahin Taş, Felix Hauser, Christoph Stiller
Motion planning involves decision making among combinatorial maneuver variants in urban driving. A planner must consider uncertainties and associated risks of the maneuver variants…
Tackling Existence Probabilities of Objects with Motion Planning for Automated Urban Driving
Omer Sahin Tas, Christoph Stiller
Motion planners take uncertain information about the environment as an input. The environment information is often quite noisy and has a tendency to contain false positive object d…
Limited Visibility and Uncertainty Aware Motion Planning for Automated Driving
Omer Sahin Tas, Christoph Stiller
Adverse weather conditions and occlusions in urban environments result in impaired perception. The uncertainties are handled in different modules of an automated vehicle, ranging f…