exploration

Create HTML profiling reports from pandas DataFrame objects

🎈 Simple reactive notebooks for Julia

Space exploration, trading, and combat game.

Visualize and compare datasets, target values and associations, with one line of code.

The purpose of this project is to share knowledge on how awesome Streamlit is and can be

[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning

A game of lonely space adventure

Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"

A ROS package that implements a multi-robot RRT-based map exploration algorithm. It also has the image-based frontier detection that uses image processing to extract frontier points.

This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.

A curated list of awesome exploration RL resources (continually updated)

Pytorch code for NeurIPS-20 Paper "Object Goal Navigation using Goal-Oriented Semantic Exploration"

Efficient local and global exploration on submap collections with changing past pose estimates.

[ICML 2019] TensorFlow Code for Self-Supervised Exploration via Disagreement

A modularized multi-robot SLAM system with elevation mapping and a costmap converter for easy navigation. Different odometry and loop closure algorithms can be easily integrated into the system.

Capture all information throughout your model's development in a reproducible way and tie results directly to the model code!

This work contains a modified version of cartographer_frontier_detection and rrt_exploration. We implement an active exploration process and improve its robustness and performance. More details are described in the paper "Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration" (IROS2020).

HouseExpo: A Large-scale 2D Indoor Layout Dataset

Planning for robotic exploration based on forward simulation

DefSLAM: Tracking and Mapping of Deforming Scenes from Monocular Sequences. J.Lamarca, S. Parashar, A. Bartoli & J.M.M. Montiel