Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

update tracking tools #6

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

update tracking tools #6

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
3 changes: 3 additions & 0 deletions papers.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,9 @@ Awesome Papers
--------------

Papers and implementations of papers that could have use in robotics. Implementations here may not be actively developed. While implementations may often be the author's original implementation, that isn't always the case.
- [BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects](https://bundlesdf.github.io/) - 2023 - 6D pose tracking and 3D reconstruction of unknown objects
- [BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models](https://github.com/wenbowen123/BundleTrack) - 2021 - 6D object pose tracking without needing any CAD models
- [se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains](https://github.com/wenbowen123/iros20-6d-pose-tracking) - 2020 - 6D object pose tracking trained solely on synthetic data
- ["Good Robot!": Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer](https://github.com/jhu-lcsr/good_robot) - 2020 - Real robot learns to complete multi-step tasks like table clearing, making stacks, and making rows in <20k simulated actions. [paper](https://arxiv.org/abs/1909.11730) (disclaimer: @ahundt is first author) [!["Good Robot!": Efficient Reinforcement Learning for Multi Step Visual Tasks via Reward Shaping](https://img.youtube.com/vi/MbCuEZadkIw/0.jpg)](https://youtu.be/MbCuEZadkIw)

- [Transporter Networks: Rearranging the Visual World for Robotic Manipulation](https://transporternets.github.io/) - [Ravens Simulator code](https://github.com/google-research/google-research/tree/master/ravens) - 2020 - Ravens is a collection of simulated tasks in PyBullet for learning vision-based robotic manipulation, with emphasis on pick and place. It features a Gym-like API with 10 tabletop rearrangement tasks, each with (i) a scripted oracle that provides expert demonstrations (for imitation learning), and (ii) reward functions that provide partial credit (for reinforcement learning).
Expand Down