Boris Ivanovic | DeepAI

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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...

0 Yuxiao Chen, et al. ∙

∙ 12/13/2022

DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles

Autonomous vehicle (AV) stacks are typically built in a modular fashion,...

0 Peter Karkus, et al. ∙

∙ 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...

0 Filippos Christianos, et al. ∙

∙ 10/11/2022

Robust and Controllable Object-Centric Learning through Energy-based Models

Humans are remarkably good at understanding and reasoning about complex ...

12 Ruixiang Zhang, et al. ∙

∙ 09/23/2022

Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning

Learning-based behavior prediction methods are increasingly being deploy...

0 Boris Ivanovic, et al. ∙

∙ 08/26/2022

BITS: Bi-level Imitation for Traffic Simulation

Simulation is the key to scaling up validation and verification for robo...

2 Danfei Xu, et al. ∙

∙ 07/25/2022

Task-Relevant Failure Detection for Trajectory Predictors in Autonomous Vehicles

In modern autonomy stacks, prediction modules are paramount to planning ...

0 Alec Farid, et al. ∙

∙ 06/18/2022

ScePT: Scene-consistent, Policy-based Trajectory Predictions for Planning

Trajectory prediction is a critical functionality of autonomous systems ...

0 Yuxiao Chen, et al. ∙

∙ 10/18/2021

MTP: Multi-Hypothesis Tracking and Prediction for Reduced Error Propagation

Recently, there has been tremendous progress in developing each individu...

0 Xinshuo Weng, et al. ∙

∙ 10/07/2021

Injecting Planning-Awareness into Prediction and Detection Evaluation

Detecting other agents and forecasting their behavior is an integral par...

0 Boris Ivanovic, et al. ∙

∙ 10/07/2021

Propagating State Uncertainty Through Trajectory Forecasting

Uncertainty pervades through the modern robotic autonomy stack, with nea...

0 Boris Ivanovic, et al. ∙

∙ 09/28/2021

Sample-Efficient Safety Assurances using Conformal Prediction

When deploying machine learning models in high-stakes robotics applicati...

0 Rachel Luo, et al. ∙

∙ 07/21/2021

Rethinking Trajectory Forecasting Evaluation

Forecasting the behavior of other agents is an integral part of the mode...

0 Boris Ivanovic, et al. ∙

∙ 04/26/2021

Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty

Reasoning about the future behavior of other agents is critical to safe ...

3 Boris Ivanovic, et al. ∙

∙ 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 ...

0 Simon Schaefer, et al. ∙

∙ 10/19/2020

Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders

Discrete latent spaces in variational autoencoders have been shown to ef...

0 Masha Itkina, et al. ∙

∙ 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...

0 Boris Ivanovic, et al. ∙

∙ 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...

0 Haruki Nishimura, et al. ∙

∙ 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 ...

0 Boris Ivanovic, et al. ∙

∙ 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...

0 Tim Salzmann, et al. ∙

∙ 10/17/2019

Map-Predictive Motion Planning in Unknown Environments

Algorithms for motion planning in unknown environments are generally lim...

0 Amine Elhafsi, et al. ∙

∙ 10/14/2018

Modeling Multimodal Dynamic Spatiotemporal Graphs

Spatiotemporal graphs (STGs) are a powerful tool for modeling multi-agen...

0 Boris Ivanovic, et al. ∙

∙ 06/16/2018

BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning

Model-free Reinforcement Learning (RL) offers an attractive approach to ...

0 Boris Ivanovic, et al. ∙

∙ 03/06/2018

Generative Modeling of Multimodal Multi-Human Behavior

This work presents a methodology for modeling and predicting human behav...

0 Boris Ivanovic, et al. ∙