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Found 5 papers, 2 papers with code
Robot Navigation in Constrained Pedestrian Environments using Reinforcement Learning
Navigating fluently around pedestrians is a necessary capability for mobile robots deployed in human environments, such as buildings and homes.
JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Dataset
In this work we present JRMOT, a novel 3D MOT system that integrates information from RGB images and 3D point clouds to achieve real-time, state-of-the-art tracking performance.
Ranked #8 on
Multiple Object Tracking
on KITTI Tracking test
Deep Local Trajectory Replanning and Control for Robot Navigation
We present a navigation system that combines ideas from hierarchical planning and machine learning.
GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation
We present semi-supervised deep learning approaches for traversability estimation from fisheye images.
To Go or Not To Go? A Near Unsupervised Learning Approach For Robot Navigation
It is important for robots to be able to decide whether they can go through a space or not, as they navigate through a dynamic environment.
