MixNet: Structured Deep Neural Motion Prediction for Autonomous Racing

MixNet: Structured Deep Neural Motion Prediction for Autonomous Racing

3 August 2022

Maximilian Geisslinger

Markus Lienkamp

Papers citing "MixNet: Structured Deep Neural Motion Prediction for Autonomous Racing"

7 / 7 papers shown

Title
BETTY Dataset: A Multi-modal Dataset for Full-Stack Autonomy Micah Nye Ayoub Raji Andrew Saba Eidan Erlich Robert Exley ... Ritesh Misra Matthew Sivaprakasam Marko Bertogna Deva Ramanan Sebastian A. Scherer 23 0 0 12 May 2025
Boundary-Guided Trajectory Prediction for Road Aware and Physically Feasible Autonomous Driving Ahmed Abouelazm Mianzhi Liu Christian Hubschneider Yin Wu Daniel Slieter J. M. Zöllner 26 0 0 10 May 2025
A Physics-informed End-to-End Occupancy Framework for Motion Planning of Autonomous Vehicles Shuqi Shen Junjie Yang Hongliang Lu Hui Zhong Qiming Zhang Xinhu Zheng 21 0 0 08 May 2025
Physics-Informed Neural Network for Multirotor Slung Load Systems Modeling Gil Serrano Marcelo Jacinto José Ribeiro-Gomes Joao Pinto Bruno J. Guerreiro Alexandre Bernardino Rita Cunha 17 0 0 15 May 2024
A Review of Full-Sized Autonomous Racing Vehicle Sensor Architecture Manuel Mar Vishnu Pandi Chellapandi Liangqi Yuan Ziran Wang Eric Dietz 26 2 0 04 Feb 2024
TUM autonomous motorsport: An autonomous racing software for the Indy Autonomous Challenge Johannes Betz Tobias Betz F. Fent Maximilian Geisslinger Alexander Heilmeier ... Florian Sauerbeck Tim Stahl Rainer Trauth Frederik Werner A. Wischnewski 23 60 0 31 May 2022
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 201 7,884 0 13 Jun 2015