LeCAR-Lab/model-based-diffusion
Official implementation for the paper "Model-based Diffusion for Trajectory Optimization". Model-based diffusion (MBD) is a novel diffusion-based trajectory optimization framework that employs a dynamics model to run the reverse denoising process to generate high-quality trajectories.
This tool helps robotics engineers and control system designers create highly efficient and precise movement plans for robots and autonomous systems. By inputting a system's dynamics and desired task (like a robot arm's movement or a car's path), it outputs optimized trajectories, enabling robots to perform complex actions smoothly and accurately. It's designed for those who need to improve the performance and energy efficiency of their robotic systems.
330 stars. No commits in the last 6 months.
Use this if you need to generate optimal movement paths for robotic systems or simulations with high sample efficiency and strong generalization capabilities.
Not ideal if you are looking for a simple, off-the-shelf solution for basic control problems that don't require advanced trajectory optimization.
Stars
330
Forks
31
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 27, 2025
Commits (30d)
0
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