Skip to content
arXiv Robotics — research abstracts· Yuhao Zhang, Keisuke Okumura, Ajay Shankar, Amanda Prorok·· 15 hours agoSignalEditorial score75

Denoising Multirobot Trajectories

Denoising Multirobot Trajectories

Summary

This research presents D4orm, a dynamics-aware diffusion-denoising framework for multi-robot trajectory planning.

Editorial context

The paper introduces D4orm, a dynamics-aware diffusion-denoising framework for multi-robot trajectory planning that achieves faster and more reliable solutions than sampling-based optimization methods like MPPI and learned diffusion models in both simulation and real-world deployments on quadrotors and ground robots.

Source: arXiv Robotics — research abstracts · Read original article ↗

Loading article text…

What the source reports

Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.

Source excerpts and review record

Automatically extracted; no manual editorial approval recorded.

obot coordination. Code and video: https://github.com/proroklab/d4orm

Open source S6

Source:arXiv Robotics — research abstracts · arxiv.org

Timezone · UTC

Article dates follow your selected timezone. Briefing editions use Hong Kong time (UTC+8).