most citedCompetitive Policy Optimization

2 citations · 3 across the 4 of their papers we have counts for

collaborators

8 papers

cs.CV20201 cited

Learning Accurate and Human-Like Driving using Semantic Maps and Attention

Simon Hecker, Dengxin Dai, Alexander Liniger +1

This paper investigates how end-to-end driving models can be improved to drive more accurately and human-like. To tackle the first issue we exploit semantic and visual maps from HE…

cs.LG20202 cited

Competitive Policy Optimization

Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger +2

A core challenge in policy optimization in competitive Markov decision processes is the design of efficient optimization methods with desirable convergence and stability properties…

cs.RO2020

Safe Motion Planning for Autonomous Driving using an Adversarial Road Model

Alexander Liniger, Luc van Gool

This paper presents a game-theoretic path-following formulation where the opponent is an adversary road model. This formulation allows us to compute safe sets using tools from viab…

cs.CV2020

Action Sequence Predictions of Vehicles in Urban Environments using Map and Social Context

Jan-Nico Zaech, Dengxin Dai, Alexander Liniger +1

This work studies the problem of predicting the sequence of future actions for surround vehicles in real-world driving scenarios. To this aim, we make three main contributions. The…

cs.RO2020

Optimization-Based Hierarchical Motion Planning for Autonomous Racing

José L. Vázquez, Marius Brühlmeier, Alexander Liniger +2

In this paper we propose a hierarchical controller for autonomous racing where the same vehicle model is used in a two level optimization framework for motion planning. The high-le…

eess.SY2019

Real-Time Predictive Control for Precision Machining

Alexander Liniger, Luca Varano, Alisa Rupenyan +1

Precise positioning and fast traversal times are crucial in achieving high productivity and scale in machining. This paper compares two optimization-based predictive control approa…