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09/01/2023
Reinforcement Learning with Human Feedback for Realistic Traffic Simulation
In light of the challenges and costs of real-world testing, autonomous v...
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07/26/2023
trajdata: A Unified Interface to Multiple Human Trajectory Datasets
The field of trajectory forecasting has grown significantly in recent ye...
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07/16/2023
Language Conditioned Traffic Generation
Simulation forms the backbone of modern self-driving development. Simula...
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06/10/2023
Language-Guided Traffic Simulation via Scene-Level Diffusion
Realistic and controllable traffic simulation is a core capability that ...
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01/27/2023
Tree-structured Policy Planning with Learned Behavior Models
Autonomous vehicles (AVs) need to reason about the multimodal behavior o...
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12/13/2022
DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles
Autonomous vehicle (AV) stacks are typically built in a modular fashion,...
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10/26/2022
Planning with Occluded Traffic Agents using Bi-Level Variational Occlusion Models
Reasoning with occluded traffic agents is a significant open challenge f...
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10/11/2022
Robust and Controllable Object-Centric Learning through Energy-based Models
Humans are remarkably good at understanding and reasoning about complex ...
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09/23/2022
Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning
Learning-based behavior prediction methods are increasingly being deploy...
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08/26/2022
BITS: Bi-level Imitation for Traffic Simulation
Simulation is the key to scaling up validation and verification for robo...
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07/25/2022
Task-Relevant Failure Detection for Trajectory Predictors in Autonomous Vehicles
In modern autonomy stacks, prediction modules are paramount to planning ...
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06/18/2022
ScePT: Scene-consistent, Policy-based Trajectory Predictions for Planning
Trajectory prediction is a critical functionality of autonomous systems ...
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10/18/2021
MTP: Multi-Hypothesis Tracking and Prediction for Reduced Error Propagation
Recently, there has been tremendous progress in developing each individu...
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10/07/2021
Injecting Planning-Awareness into Prediction and Detection Evaluation
Detecting other agents and forecasting their behavior is an integral par...
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10/07/2021
Propagating State Uncertainty Through Trajectory Forecasting
Uncertainty pervades through the modern robotic autonomy stack, with nea...
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09/28/2021
Sample-Efficient Safety Assurances using Conformal Prediction
When deploying machine learning models in high-stakes robotics applicati...
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07/21/2021
Rethinking Trajectory Forecasting Evaluation
Forecasting the behavior of other agents is an integral part of the mode...
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04/26/2021
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty
Reasoning about the future behavior of other agents is critical to safe ...
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12/02/2020
Leveraging Neural Network Gradients within Trajectory Optimization for Proactive Human-Robot Interactions
To achieve seamless human-robot interactions, robots need to intimately ...
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10/19/2020
Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders
Discrete latent spaces in variational autoencoders have been shown to ef...
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09/16/2020
MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control
Reasoning about human motion is a core component of modern human-robot i...
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09/12/2020
Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction
This paper presents a novel online framework for safe crowd-robot intera...
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08/10/2020
Multimodal Deep Generative Models for Trajectory Prediction: A Conditional Variational Autoencoder Approach
Human behavior prediction models enable robots to anticipate how humans ...
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01/09/2020
Trajectron++: Multi-Agent Generative Trajectory Forecasting With Heterogeneous Data for Control
Reasoning about human motion through an environment is an important prer...
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10/17/2019
Map-Predictive Motion Planning in Unknown Environments
Algorithms for motion planning in unknown environments are generally lim...
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10/14/2018
Modeling Multimodal Dynamic Spatiotemporal Graphs
Spatiotemporal graphs (STGs) are a powerful tool for modeling multi-agen...
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06/16/2018
BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning
Model-free Reinforcement Learning (RL) offers an attractive approach to ...
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03/06/2018
