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A Safe Hierarchical Planning Framework for Complex Driving Scenarios based on Reinforcement Learning
Autonomous vehicles need to handle various traffic conditions and make s...
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Interaction-Aware Behavior Planning for Autonomous Vehicles Validated with Real Traffic Data
Autonomous vehicles (AVs) need to interact with other traffic participan...
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Labels Are Not Perfect: Inferring Spatial Uncertainty in Object Detection
The availability of many real-world driving datasets is a key reason beh...
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Sparse R-CNN: End-to-End Object Detection with Learnable Proposals
We present Sparse R-CNN, a purely sparse method for object detection in ...
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Prediction-Based Reachability for Collision Avoidance in Autonomous Driving
Safety is an important topic in autonomous driving since any collision m...
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COCOI: Contact-aware Online Context Inference for Generalizable Non-planar Pushing
General contact-rich manipulation problems are long-standing challenges ...
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Learning Dense Rewards for Contact-Rich Manipulation Tasks
Rewards play a crucial role in reinforcement learning. To arrive at the ...
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IDE-Net: Interactive Driving Event and Pattern Extraction from Human Data
Autonomous vehicles (AVs) need to share the road with multiple, heteroge...
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Alternating Direction Method of Multipliers for Constrained Iterative LQR in Autonomous Driving
In the context of autonomous driving, the iterative linear quadratic reg...
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Socially-Compatible Behavior Design of Autonomous Vehicles with Verification on Real Human Data
As more and more autonomous vehicles (AVs) are being deployed on public ...
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Bounded Risk-Sensitive Markov Game and Its Inverse Reward Learning Problem
Classical game-theoretic approaches for multi-agent systems in both the ...
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Expressing Diverse Human Driving Behavior with Probabilistic Rewards and Online Inference
In human-robot interaction (HRI) systems, such as autonomous vehicles, u...
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Data-Driven Multi-Objective Controller Optimization for a Magnetically-Levitated Nanopositioning System
The performance achieved with traditional model-based control system des...
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Towards Better Performance and More Explainable Uncertainty for 3D Object Detection of Autonomous Vehicles
In this paper, we propose a novel form of the loss function to increase ...
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Efficient Sampling-Based Maximum Entropy Inverse Reinforcement Learning with Application to Autonomous Driving
In the past decades, we have witnessed significant progress in the domai...
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In Proximity of ReLU DNN, PWA Function, and Explicit MPC
Rectifier (ReLU) deep neural networks (DNN) and their connection with pi...
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Visual Transformers: Token-based Image Representation and Processing for Computer Vision
Computer vision has achieved great success using standardized image repr...
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Cascade Attribute Network: Decomposing Reinforcement Learning Control Policies using Hierarchical Neural Networks
Reinforcement learning methods have been developed to achieve great succ...
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Guided Policy Search Model-based Reinforcement Learning for Urban Autonomous Driving
In this paper, we continue our prior work on using imitation learning (I...
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Scenario-Transferable Semantic Graph Reasoning for Interaction-Aware Probabilistic Prediction
Accurately predicting the possible behaviors of traffic participants is ...
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SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation
LiDAR point-cloud segmentation is an important problem for many applicat...
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EvolveGraph: Heterogeneous Multi-Agent Multi-Modal Trajectory Prediction with Evolving Interaction Graphs
Multi-agent interacting systems are prevalent in the world, from pure ph...
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End-to-end Autonomous Driving Perception with Sequential Latent Representation Learning
Current autonomous driving systems are composed of a perception system a...
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Inferring Spatial Uncertainty in Object Detection
The availability of real-world datasets is the prerequisite to develop o...
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Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network
Effective understanding of the environment and accurate trajectory predi...
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Experimental Evaluation of Human Motion Prediction: Toward Safe and Efficient Human Robot Collaboration
Human motion prediction is non-trivial in modern industrial settings. Ac...
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Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning
Unlike popular modularized framework, end-to-end autonomous driving seek...
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AutoScale: Learning to Scale for Crowd Counting
Crowd counting in images is a widely explored but challenging task. Thou...
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UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes
Mapping and localization is a critical module of autonomous driving, and...
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Robust Feature-Based Point Registration Using Directional Mixture Model
This paper presents a robust probabilistic point registration method for...
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Adaptive Probabilistic Vehicle Trajectory Prediction Through Physically Feasible Bayesian Recurrent Neural Network
Probabilistic vehicle trajectory prediction is essential for robust safe...
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Multiple criteria decision-making for lane-change model
Simulation has long been an essential part of testing autonomous driving...
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Online Learning in Planar Pushing with Combined Prediction Model
Pushing is a useful robotic capability for positioning and reorienting o...
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INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps
Behavior-related research areas such as motion prediction/planning, repr...
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Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving
Accurately tracking and predicting behaviors of surrounding objects are ...
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Generic Prediction Architecture Considering both Rational and Irrational Driving Behaviors
Accurately predicting future behaviors of surrounding vehicles is an ess...
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Interpretable Modelling of Driving Behaviors in Interactive Driving Scenarios based on Cumulative Prospect Theory
Understanding human driving behavior is important for autonomous vehicle...
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Conditional Generative Neural System for Probabilistic Trajectory Prediction
Effective understanding of the environment and accurate trajectory predi...
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Behavior Planning of Autonomous Cars with Social Perception
Autonomous cars have to navigate in dynamic environment which can be ful...
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Coordination and Trajectory Prediction for Vehicle Interactions via Bayesian Generative Modeling
Coordination recognition and subtle pattern prediction of future traject...
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Model-free Deep Reinforcement Learning for Urban Autonomous Driving
Urban autonomous driving decision making is challenging due to complex r...
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Optimization Model for Planning Precision Grasps with Multi-Fingered Hands
Precision grasps with multi-fingered hands are important for precise pla...
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Interaction-aware Decision Making with Adaptive Strategies under Merging Scenarios
In order to drive safely and efficiently under merging scenarios, autono...
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Interaction-aware Multi-agent Tracking and Probabilistic Behavior Prediction via Adversarial Learning
In order to enable high-quality decision making and motion planning of i...
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Multi-modal Probabilistic Prediction of Interactive Behavior via an Interpretable Model
For autonomous agents to successfully operate in real world, the ability...
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Towards Better Human Robot Collaboration with Robust Plan Recognition and Trajectory Prediction
Human robot collaboration (HRC) is becoming increasingly important as th...
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Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safety
The decision and planning system for autonomous driving in urban environ...
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Efficient Grasp Planning and Execution with Multi-Fingered Hands by Surface Fitting
This paper introduces a framework to plan grasps with multi-fingered han...
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Nonparametric Inverse Dynamic Models for Multimodal Interactive Robots
Direct design of a robot's rendered dynamics, such as in impedance contr...
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Zero-shot Deep Reinforcement Learning Driving Policy Transfer for Autonomous Vehicles based on Robust Control
Although deep reinforcement learning (deep RL) methods have lots of stre...
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