# Preprint demonstrates adaptive robot control with GPU planning and drone tests

_Published Friday, October 16, 2026 at 6:21 AM EDT · Science, Robotics · Latest · Tier 2 — Notable_

Researchers report a robot control framework that accounts for what a robot will learn during future movement, with a physical Crazyflie drone demonstration in which it learned an uncertain dynamics parameter while stabilizing in flight. The A-SLS framework is described in an arXiv preprint.

The method tracks relationships between disturbances, parameter errors and estimate updates to bound the states a robot could reach. A GPU solver supports real-time planning. The researchers also report scaling to quadruped whole-body control with 61 states, 8 uncertain parameters and 12 control inputs; the stated hardware demonstration uses the drone.

## Sources

- [cs.LG updates on arXiv.org](https://arxiv.org/abs/2610.20925)

---
Canonical: https://techandbusiness.org/newswire/Ym4tnpf78SYcr9xkepQArO
Published: 2026-10-16T10:21:27.394Z
Story chronology: 2026-10-16T04:00:00.000Z
Retrieved: 2026-10-16T12:33:37.180Z
Publisher: Tech & Business (techandbusiness.org)