Resource Constraint adaptive computing: Algorithm and optimization ARL Autonomy Stack

Overview

There is an internship opportunity at Army Research Laboratory at Aberdeen Proving Ground for graduate students with US citizenship or green card holders. The ARL team focuses on optimizing computationally expensive perception algorithms in the autonomy stack. Autonomous vehicles use sensors such as RGB cameras and Lidar to sense the environment and build world maps for autonomous maneuver. The team will develop approaches to optimize perception algorithms to fit tactical unmanned vehicles (UGVs) with limited computing resources, achieving real‑time operation and mission success.

The student will work closely with ARL researchers to optimize and integrate containerized machine‑learning algorithms into UGVs and evaluate model performance in lab and field tests.

• Use Python, C++, and software repositories to develop solutions.
• Optimize deep learning perception algorithms.
• Use containerization technologies such as Docker to create Docker images for perception algorithms to be evaluated in a ROS environment.
• Deploy machine learning algorithms in a ROS environment on UGVs.
• Document and publish the results in technical reports or conference papers.

Candidate does not need to have all skills right now but must be willing to learn new technology.

• Currently pursuing a Master’s or Doctoral degree.
• Graduate students with US citizenship or green card holders.

DEVCOM Army Research Laboratory

ARL-R-CISD-300163-NCCS