Aim My Robot: Precision Local Navigation to Any Object
Xiangyun Meng, Xuning Yang, Sanghun Jung, Fabio Ramos, Srid Sadhan Jujjavarapu, Sanjoy Paul, Dieter Fox
Abstract
Existing navigation systems mostly consider “success” when the robot reaches within 1 m radius to a goal. This precision is insufficient for emerging applications where a robot needs to be positioned precisely relative to an object for downstream tasks, such as docking, inspection, and manipulation. To this end, we design and implement <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Aim-My-Robot</i> (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AMR</i>), a local navigation system that enables a robot to reach any object in its vicinity at the desired relative pose, with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">centimeter-level accuracy</i>. AMR achieves high accuracy and robustness by leveraging multi-modal sensors, precise action prediction, and is trained on large-scale photorealistic data generated in simulation. AMR shows strong sim2real transfer and can adapt to different robot kinematics and unseen objects with little to no fine-tuning.
BibTeX
@inproceedings{ral2025_aimmyrobotprecis,
title = {Aim My Robot: Precision Local Navigation to Any Object},
author = {Xiangyun Meng and Xuning Yang and Sanghun Jung and Fabio Ramos and Srid Sadhan Jujjavarapu and Sanjoy Paul and Dieter Fox},
booktitle = {RA-L 2025},
year = {2025}
}