intuitive-robots/MoDE_Diffusion_Policy
[ICLR 25] Code for "Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning"
This project offers a method for training robotic agents to perform a variety of tasks more efficiently and accurately. By taking in diverse robotic demonstration datasets, it outputs policies that enable robots to execute complex sequences of actions with high success rates. This is primarily useful for robotics researchers and engineers who develop and deploy advanced robotic systems for automation and manipulation.
117 stars. No commits in the last 6 months.
Use this if you need to train a robotic agent to learn multiple complex manipulation skills from various demonstration datasets and achieve high performance across these tasks.
Not ideal if you are looking for a simple, out-of-the-box solution for basic robot control or if you do not have access to diverse robot demonstration data.
Stars
117
Forks
16
Language
C++
License
MIT
Category
Last pushed
May 16, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/intuitive-robots/MoDE_Diffusion_Policy"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ZhengYinan-AIR/Diffusion-Planner
[ICLR 2025 Oral] The official implementation of "Diffusion-Based Planning for Autonomous Driving...
caio-freitas/GraphDiffusionImitate
Diffusion-based graph generative policies for imitation learning in robotics tasks 🧠🤖
LeCAR-Lab/model-based-diffusion
Official implementation for the paper "Model-based Diffusion for Trajectory Optimization"....
Weixy21/SafeDiffuser
Safe Planning with Diffusion Probabilistic Models
AI4Science-WestlakeU/diffphycon
[NeurIPS2024] DiffPhyCon uses generative models to control complex physical systems