Rethinking integration of prediction and planning in deep learning-based automated driving systems: a review
Automated driving has the potential to revolutionize personal, public, and freight mobility.
Besides the enormous challenge of perception, ie accurately perceiving the environment …
Besides the enormous challenge of perception, ie accurately perceiving the environment …
Uncovering the missing pattern: Unified framework towards trajectory imputation and prediction
Trajectory prediction is a crucial undertaking in understanding entity movement or human
behavior from observed sequences. However, current methods often assume that the …
behavior from observed sequences. However, current methods often assume that the …
The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Review
Automated driving has the potential to revolutionize personal, public, and freight mobility.
Beside accurately perceiving the environment, automated vehicles must plan a safe …
Beside accurately perceiving the environment, automated vehicles must plan a safe …
Adapting to length shift: Flexilength network for trajectory prediction
Trajectory prediction plays an important role in various applications including autonomous
driving robotics and scene understanding. Existing approaches mainly focus on developing …
driving robotics and scene understanding. Existing approaches mainly focus on developing …
On a Connection between Differential Games, Optimal Control, and Energy-based Models for Multi-Agent Interactions
Game theory offers an interpretable mathematical framework for modeling multi-agent
interactions. However, its applicability in real-world robotics applications is hindered by …
interactions. However, its applicability in real-world robotics applications is hindered by …
MixCycle: Mixup Assisted Semi-Supervised 3D Single Object Tracking with Cycle Consistency
Q Wu, J Yang, K Sun, C Zhang… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract 3D single object tracking (SOT) is an indispensable part of automated driving.
Existing approaches rely heavily on large, densely labeled datasets. However, annotating …
Existing approaches rely heavily on large, densely labeled datasets. However, annotating …
Do large language models pay similar attention like human programmers when generating code?
Large Language Models (LLMs) have recently been widely used for code generation. Due
to the complexity and opacity of LLMs, little is known about how these models generate …
to the complexity and opacity of LLMs, little is known about how these models generate …
Deciphering Movement: Unified Trajectory Generation Model for Multi-Agent
Understanding multi-agent behavior is critical across various fields. The conventional
approach involves analyzing agent movements through three primary tasks: trajectory …
approach involves analyzing agent movements through three primary tasks: trajectory …
MixFormer: A Self-Attentive Convolutional Network for 3D Mesh Object Recognition
L Huang, J Zhao, Y Chen - Algorithms, 2023 - mdpi.com
3D mesh as a complex data structure can provide effective shape representation for 3D
objects, but due to the irregularity and disorder of the mesh data, it is difficult for …
objects, but due to the irregularity and disorder of the mesh data, it is difficult for …
Nonlinear modeling between steering wheel angle and front wheel angle for unmanned vehicle
K Liu, Y Zeng, M Zhu, Q Yang, L Tao… - 2023 China Automation …, 2023 - ieeexplore.ieee.org
Unmanned vehicles have attracted notable attention in recent years. Trajectory control is
one of the core problems of unmanned vehicles. It is meaningful to establish a precise …
one of the core problems of unmanned vehicles. It is meaningful to establish a precise …