# OMPL Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/ompl
> Markdown URL: https://aitinkerers.org/technologies/ompl.md
> Technology record last updated: 2026-02-25T04:54:38Z
> Generated: 2026-09-22T16:38:12Z

A high-performance C++ library providing over 50 sampling-based motion planning algorithms for complex robotic systems.

OMPL (Open Motion Planning Library) provides a collection of state-of-the-art sampling-based algorithms (like RRT* and PRM) for high-dimensional configuration spaces. Developed at Rice University and integrated into the MoveIt framework, it handles the heavy lifting of pathfinding for systems ranging from 7-DOF industrial arms to autonomous mobile bases. The library remains hardware-agnostic by decoupling the planning logic from collision checking and state validation. With a clean C++ API and Python bindings, OMPL is the go-to engine for developers building reliable motion pipelines in ROS and beyond.

- Official technology site: https://ompl.kavrakilab.org/
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Akomi - Automating prior authorization for healthcare providers](https://london.aitinkerers.org/talks/rsvp_Yhlw8_YJBTA)

We are building Akomi, a vertical AI agent that looks to handle Revenue Cycle Management for small to medium sized healthcare clinics in the US. We're starting with automating the "Prior Authorization" flow, which (from our research) would alleviate a significant administrative burden for healthcare providers.

- Event context: AI Tinkerers London - December Meetup 🎄 — 2024-12-04 — London
- Public talk page: https://london.aitinkerers.org/talks/rsvp_Yhlw8_YJBTA

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