Publications (43)
Optimization-Based Autonomous Racing of 1:43 Scale RC Cars
Alexander Liniger, Alexander Domahidi, Manfred Morari
This paper describes autonomous racing of RC race cars based on mathematical optimization. Using a dynamical model of the vehicle, control inputs are computed by receding horizon b…
Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models
Jose L. Vazquez, Alexander Liniger, Wilko Schwarting +2
In most classical Autonomous Vehicle (AV) stacks, the prediction and planning layers are separated, limiting the planner to react to predictions that are not informed by the planne…
Decoder Fusion RNN: Context and Interaction Aware Decoders for Trajectory Prediction
Edoardo Mello Rella, Jan-Nico Zaech, Alexander Liniger +1
Forecasting the future behavior of all traffic agents in the vicinity is a key task to achieve safe and reliable autonomous driving systems. It is a challenging problem as agents a…
Spectral Tensor Train Parameterization of Deep Learning Layers
Anton Obukhov, Maxim Rakhuba, Alexander Liniger +4
We study low-rank parameterizations of weight matrices with embedded spectral properties in the Deep Learning context. The low-rank property leads to parameter efficiency and permi…
P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior
Vaishakh Patil, Christos Sakaridis, Alexander Liniger +1
Monocular depth estimation is vital for scene understanding and downstream tasks. We focus on the supervised setup, in which ground-truth depth is available only at training time.…
Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds
Ayoub Raji, Alexander Liniger, Andrea Giove +6
This paper presents a multi-layer motion planning and control architecture for autonomous racing, capable of avoiding static obstacles, performing active overtakes, and reaching ve…
End-to-End Learning of Multi-category 3D Pose and Shape Estimation
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
In this paper, we study the representation of the shape and pose of objects using their keypoints. Therefore, we propose an end-to-end method that simultaneously detects 2D keypoin…
Prior Based Online Lane Graph Extraction from Single Onboard Camera Image
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
The local road network information is essential for autonomous navigation. This information is commonly obtained from offline HD-Maps in terms of lane graphs. However, the local ro…
Learnable Online Graph Representations for 3D Multi-Object Tracking
Jan-Nico Zaech, Dengxin Dai, Alexander Liniger +2
Tracking of objects in 3D is a fundamental task in computer vision that finds use in a wide range of applications such as autonomous driving, robotics or augmented reality. Most re…
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…
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…
Quantifying Data Augmentation for LiDAR based 3D Object Detection
Martin Hahner, Dengxin Dai, Alexander Liniger +1
In this work, we shed light on different data augmentation techniques commonly used in Light Detection and Ranging (LiDAR) based 3D Object Detection. For the bulk of our experiment…
A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differential
Ayoub Raji, Nicola Musiu, Alessandro Toschi +7
In this paper, we present a novel formulation to model the effects of a locked differential on the lateral dynamics of an autonomous open-wheel racecar. The model is used in a Mode…
er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds
Ayoub Raji, Danilo Caporale, Francesco Gatti +15
The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at unprecedented speed and in head-to-head scenario, using…
End-to-End Urban Driving by Imitating a Reinforcement Learning Coach
Zhejun Zhang, Alexander Liniger, Dengxin Dai +2
End-to-end approaches to autonomous driving commonly rely on expert demonstrations. Although humans are good drivers, they are not good coaches for end-to-end algorithms that deman…
Online Lane Graph Extraction from Onboard Video
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
Autonomous driving requires a structured understanding of the surrounding road network to navigate. One of the most common and useful representation of such an understanding is don…
Cautious NMPC with Gaussian Process Dynamics for Autonomous Miniature Race Cars
Lukas Hewing, Alexander Liniger, Melanie N. Zeilinger
This paper presents an adaptive high performance control method for autonomous miniature race cars. Racing dynamics are notoriously hard to model from first principles, which is ad…
Learning from Simulation, Racing in Reality
Eugenio Chisari, Alexander Liniger, Alisa Rupenyan +2
We present a reinforcement learning-based solution to autonomously race on a miniature race car platform. We show that a policy that is trained purely in simulation using a relativ…
Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding
Zhejun Zhang, Alexander Liniger, Christos Sakaridis +2
The real-world deployment of an autonomous driving system requires its components to run on-board and in real-time, including the motion prediction module that predicts the future…
Object-centric Cross-modal Feature Distillation for Event-based Object Detection
Lei Li, Alexander Liniger, Mario Millhaeusler +3
Event cameras are gaining popularity due to their unique properties, such as their low latency and high dynamic range. One task where these benefits can be crucial is real-time obj…
Learning a Curve Guardian for Motorcycles
Simon Hecker, Alexander Liniger, Henrik Maurenbrecher +2
Up to 17% of all motorcycle accidents occur when the rider is maneuvering through a curve and the main cause of curve accidents can be attributed to inappropriate speed and wrong i…
Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fields
Soomin Lee, Le Chen, Jiahao Wang +3
In this paper, we tackle the problem of active robotic 3D reconstruction of an object. In particular, we study how a mobile robot with an arm-held camera can select a favorable num…
Real-Time Control for Autonomous Racing Based on Viability Theory
Alexander Liniger, John Lygeros
In this paper we consider autonomous driving of miniature race cars. The viability kernel is used to efficiently generate finite look-ahead trajectories that maximize progress whil…
Piecewise Planar Hulls for Semi-Supervised Learning of 3D Shape and Pose from 2D Images
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
We study the problem of estimating 3D shape and pose of an object in terms of keypoints, from a single 2D image. The shape and pose are learned directly from images collected by ca…
TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction
Zhejun Zhang, Alexander Liniger, Dengxin Dai +2
Data-driven simulation has become a favorable way to train and test autonomous driving algorithms. The idea of replacing the actual environment with a learned simulator has also be…
Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing
Johannes Betz, Hongrui Zheng, Alexander Liniger +5
The rising popularity of self-driving cars has led to the emergence of a new research field in the recent years: Autonomous racing. Researchers are developing software and hardware…
Optimization-Based Collision Avoidance
Xiaojing Zhang, Alexander Liniger, Francesco Borrelli
This paper presents a novel method for reformulating non-differentiable collision avoidance constraints into smooth nonlinear constraints using strong duality of convex optimizatio…
Vernata: Self-Supervised Learning of LiDAR Point Representations
Oliver Lemke, Alexander Liniger, Abel Gawel +1
LiDAR serves as a primary sensing modality for robots operating in outdoor environments. However, the performance of deep learning models in this domain is severely limited by the…
A Holistic Motion Planning and Control Solution to Challenge a Professional Racecar Driver
Sirish Srinivasan, Sebastian Nicolas Giles, Alexander Liniger
We present a holistically designed three layer control architecture capable of outperforming a professional driver racing the same car. Our approach focuses on the co-design of the…
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…
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…
Improving Online Lane Graph Extraction by Object-Lane Clustering
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
Autonomous driving requires accurate local scene understanding information. To this end, autonomous agents deploy object detection and online BEV lane graph extraction methods as a…
Deep Gradient Learning for Efficient Camouflaged Object Detection
Ge-Peng Ji, Deng-Ping Fan, Yu-Cheng Chou +3
This paper introduces DGNet, a novel deep framework that exploits object gradient supervision for camouflaged object detection (COD). It decouples the task into two connected branc…
Understanding Bird's-Eye View of Road Semantics using an Onboard Camera
Yigit Baran Can, Alexander Liniger, Ozan Unal +2
Autonomous navigation requires scene understanding of the action-space to move or anticipate events. For planner agents moving on the ground plane, such as autonomous vehicles, thi…
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…
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…
A Multiplicative Value Function for Safe and Efficient Reinforcement Learning
Nick Bührer, Zhejun Zhang, Alexander Liniger +2
An emerging field of sequential decision problems is safe Reinforcement Learning (RL), where the objective is to maximize the reward while obeying safety constraints. Being able to…
AMZ Driverless: The Full Autonomous Racing System
Juraj Kabzan, Miguel de la Iglesia Valls, Victor Reijgwart +19
This paper presents the algorithms and system architecture of an autonomous racecar. The introduced vehicle is powered by a software stack designed for robustness, reliability, and…
A Non-Cooperative Game Approach to Autonomous Racing
Alexander Liniger, John Lygeros
We consider autonomous racing of two cars and present an approach to formulate racing decisions as a non-cooperative non-zero-sum game. We design three different games where the pl…
Structured Bird's-Eye-View Traffic Scene Understanding from Onboard Images
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
Autonomous navigation requires structured representation of the road network and instance-wise identification of the other traffic agents. Since the traffic scene is defined on the…
Adiabatic Quantum Computing for Multi Object Tracking
Jan-Nico Zaech, Alexander Liniger, Martin Danelljan +2
Multi-Object Tracking (MOT) is most often approached in the tracking-by-detection paradigm, where object detections are associated through time. The association step naturally lead…
U-BEV: Height-aware Bird's-Eye-View Segmentation and Neural Map-based Relocalization
Andrea Boscolo Camiletto, Alfredo Bochicchio, Alexander Liniger +2
Efficient relocalization is essential for intelligent vehicles when GPS reception is insufficient or sensor-based localization fails. Recent advances in Bird's-Eye-View (BEV) segme…
Topology Preserving Local Road Network Estimation from Single Onboard Camera Image
Yigit Baran Can, Alexander Liniger, Danda Pani Paudel +1
Knowledge of the road network topology is crucial for autonomous planning and navigation. Yet, recovering such topology from a single image has only been explored in part. Furtherm…