Klaus Dietmayer

収録論文 54本 ・ フィジカルAI/ロボット学習

※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。

論文

• Toward Fully Autonomous Driving: AI, Challenges, Opportunities, and Needs
  2026/1/1
• Dynamic Objective MPC for Motion Planning of Seamless Docking Maneuvers
  2025/4/1
• Self-Assessment of Evidential Grid Map Fusion for Robust Motion Planning
  2024/9/1
• Efficient Path Planning in Large Unknown Environments with Switchable System Models for Automated Vehicles
  2023/10/1
• Advancing Frame-Dropping in Multi-Object Tracking-by-Detection Systems Through Event-Based Detection Triggering
  2023/8/1
• User Feedback and Sample Weighting for Ill-Conditioned Hand-Eye Calibration
  2023/8/1
• Joint Out-of-Distribution Detection and Uncertainty Estimation for Trajectory Prediction
  2023/8/1
• Real-Time Spatial Trajectory Planning for Urban Environments Using Dynamic Optimization
  2023/5/1
• Extrinsic Infrastructure Calibration Using the Hand-Eye Robot-World Formulation
  2023/5/1
• RESET: Revisiting Trajectory Sets for Conditional Behavior Prediction
  2023/4/1
• The Impact of Frame-Dropping on Performance and Energy Consumption for Multi-Object Tracking
  2023/4/1
• LMR: Lane Distance-Based Metric for Trajectory Prediction
  2023/4/1
• Tackling Clutter in Radar Data -- Label Generation and Detection Using PointNet++
  2023/3/1
• Exploring Navigation Maps for Learning-Based Motion Prediction
  2023/2/1
• SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks
  2023/1/1
• A Benchmark for Unsupervised Anomaly Detection in Multi-Agent Trajectories
  2022/9/1
• Situation-Aware Environment Perception for Decentralized Automation Architectures
  2022/7/1
• Identification of Threat Regions From a Dynamic Occupancy Grid Map for Situation-Aware Environment Perception
  2022/7/1
• MEAT: Maneuver Extraction from Agent Trajectories
  2022/6/1
• Self-Assessment for Single-Object Tracking in Clutter Using Subjective Logic
  2022/6/1
• CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attention
  2022/2/1
• A Multi-Task Recurrent Neural Network for End-to-End Dynamic Occupancy Grid Mapping
  2022/2/1
• Globally Optimal Multi-Scale Monocular Hand-Eye Calibration Using Dual Quaternions
  2022/1/1
• Situation-Aware Environment Perception Using a Multi-Layer Attention Map
  2021/12/1
• Attention-based Vehicle Self-Localization with HD Feature Maps
  2021/7/1
• Graph-based Motion Planning for Automated Vehicles using Multi-model Branching and Admissible Heuristics
  2021/2/1
• Online Extrinsic Calibration based on Per-Sensor Ego-Motion Using Dual Quaternions
  2021/1/1
• On-Road Motion Planning for Automated Vehicles at Ulm University
  2020/12/1
• Labels Are Not Perfect: Inferring Spatial Uncertainty in Object Detection
  2020/12/1
• A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving
  2020/11/1
• Dynamic Occupancy Grid Mapping with Recurrent Neural Networks
  2020/11/1
• Trajectory Planning for Automated Driving in Intersection Scenarios using Driver Models
  2020/10/1
• Kalman Filter Meets Subjective Logic: A Self-Assessing Kalman Filter Using Subjective Logic
  2020/7/1
• Extended Existence Probability Using Digital Maps for Object Verification
  2020/3/1
• Inferring Spatial Uncertainty in Object Detection
  2020/3/1
• Leveraging Uncertainties for Deep Multi-modal Object Detection in Autonomous Driving
  2020/2/1
• Motion Estimation in Occupancy Grid Maps in Stationary Settings Using Recurrent Neural Networks
  2019/9/1
• Can We Trust You? On Calibration of a Probabilistic Object Detector for Autonomous Driving
  2019/9/1
• Towards Courteous Behavior and Trajectory Planning for Automated Driving
  2019/7/1
• Robust Semantic Segmentation in Adverse Weather Conditions by means of Sensor Data Fusion
  2019/5/1
• Training a Fast Object Detector for LiDAR Range Images Using Labeled Data from Sensors with Higher Resolution
  2019/5/1
• DeepLocalization: Landmark-based Self-Localization with Deep Neural Networks
  2019/4/1
• Fusion of Object Tracking and Dynamic Occupancy Grid Map
  2019/4/1
• Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges
  2019/2/1
• Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector
  2019/1/1
• Environment Perception Framework Fusing Multi-Object Tracking, Dynamic Occupancy Grid Maps and Digital Maps
  2018/12/1
• Multi-Object Tracking with Interacting Vehicles and Road Map Information
  2018/12/1
• Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection
  2018/9/1
• Deep Object Tracking on Dynamic Occupancy Grid Maps Using RNNs
  2018/5/1
• Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection
  2018/4/1
• Object Detection on Dynamic Occupancy Grid Maps Using Deep Learning and Automatic Label Generation
  2018/2/1
• Tracking Multiple Vehicles Using a Variational Radar Model
  2017/11/1
• Dynamic Occupancy Grid Prediction for Urban Autonomous Driving: A Deep Learning Approach with Fully Automatic Labeling
  2017/5/1
• A Random Finite Set Approach for Dynamic Occupancy Grid Maps with Real-Time Application
  2016/5/1