Integrating kinematics and environment context into deep inverse reinforcement learning for predicting off-road vehicle trajectories

16 October 2018

Papers citing "Integrating kinematics and environment context into deep inverse reinforcement learning for predicting off-road vehicle trajectories"

9 / 9 papers shown

Title
Energy-based Legged Robots Terrain Traversability Modeling via Deep Inverse Reinforcement Learning Lu Gan J. Grizzle Ryan Eustice Maani Ghaffari 32 28 0 07 Jul 2022
An efficient Deep Spatio-Temporal Context Aware decision Network (DST-CAN) for Predictive Manoeuvre Planning Jayabrata Chowdhury Suresh Sundaram Nishanth Rao N. Sundararajan 23 2 0 20 May 2022
Spatiotemporal Costmap Inference for MPC via Deep Inverse Reinforcement Learning Keuntaek Lee David Isele Evangelos A. Theodorou S. Bae 34 24 0 17 Jan 2022
AGPNet -- Autonomous Grading Policy Network Chana Ross Yakov Miron Yuval Goldfracht Dotan Di Castro 50 3 0 20 Dec 2021
Trajectory Prediction in Autonomous Driving with a Lane Heading Auxiliary Loss Ross Greer Nachiket Deo Mohan M. Trivedi 35 46 0 12 Nov 2020
Trajectory Planning for Autonomous Vehicles Using Hierarchical Reinforcement Learning Kaleb Ben Naveed Zhiqian Qiao John M. Dolan 17 55 0 09 Nov 2020
Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans Nachiket Deo Mohan M. Trivedi 24 150 0 03 Jan 2020
Off-road Autonomous Vehicles Traversability Analysis and Trajectory Planning Based on Deep Inverse Reinforcement Learning Zeyu Zhu Nan Li Ruoyu Sun Huijing Zhao Donghao Xu 29 32 0 16 Sep 2019
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation Adam Paszke Abhishek Chaurasia Sangpil Kim Eugenio Culurciello SSeg 235 2,059 0 07 Jun 2016