There are 7 repositories under manipulation topic.
A Fast & Light Virtual DOM Alternative
Central repository for tools, tutorials, resources, and documentation for robotics simulation in Unity.
Study guides for MIT's 15.003 Data Science Tools
A comprehensive list of Implicit Representations and NeRF papers relating to Robotics/RL domain, including papers, codes, and related websites
A cross-platform and ultrafast toolkit for FASTA/Q file manipulation
[Embodied-AI-Survey-2024] Paper list and projects for Embodied AI
Train robotic agents to learn to plan pushing and grasping actions for manipulation with deep reinforcement learning.
BruteSploit is a collection of method for automated Generate, Bruteforce and Manipulation wordlist with interactive shell. That can be used during a penetration test to enumerate and maybe can be used in CTF for manipulation,combine,transform and permutation some words or file text :p
[IROS 2021] BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models
A curated list of 3D Vision papers relating to Robotics domain in the era of large models i.e. LLMs/VLMs, inspired by awesome-computer-vision, including papers, codes, and related websites
Train robotic agents to learn pick and place with deep learning for vision-based manipulation in PyBullet. Transporter Nets, CoRL 2020.
Code for "Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation"
No Maintenance Intended
PyBullet Planning
😎 A curated list of awesome mobile robots study resources based on ROS (including SLAM, odometry and navigation, manipulation)
Stream-based library for parsing and manipulating subtitle files
PDDLStream: Integrating Symbolic Planners and Blackbox Samplers
[IROS 2020] se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains
Isomorphic hyperHTML
[ICRA 2022] CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation
Benchmarking Knowledge Transfer in Lifelong Robot Learning
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
MIT-Princeton Vision Toolbox for Robotic Pick-and-Place at the Amazon Robotics Challenge 2017 - Robotic Grasping and One-shot Recognition of Novel Objects with Deep Learning.
Pytorch code for ICRA'22 paper: "Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation"
paper list of robotic grasping and some related works
Magic potions to clean and transform your data 🧙